Research fellow jobs in Hayward, CA

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

⚡ Research Scientists/Engineers (all levels) 🔍 Focus on Vision Data Infrastructure 🤖 Fundamental AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $250,000 - $600,000 salary + annual bonus Come join one of the only research institutions globally with resources to compete with top AI companies =>10s of 1000s of GPUs to explore state-of-the-art research in LLMs, Multimodal and Agentic AI. Currently seeking AI talent with expertise in building scalable pipelines for vision data to support both image/video generative training and multi-modal alignment. You'll design high-performance pipelines for large-scale image and video datasets, enabling efficient pretraining, alignment, and simulation-based data generation. Responsibilities: Vision Data Sourcing & Curation Collect and organize image and video data from open datasets and the web. Handle data cleaning, filtering, deduplication, and metadata generation. Ensure ethical and compliant data collection at scale. Processing & Augmentation Build high-throughput pipelines for vision data preprocessing (frame extraction, resolution normalization, format conversion, latent caching). Implement GPU-accelerated augmentation and distributed data loading (WebDataset, TFRecords, Parquet). Synthetic & Simulation-Based Data Generation Use simulation tools (e.g., Unreal Engine 5, Isaac Sim, Unity) to generate high-quality synthetic vision data. Create specialized datasets for VLM training, visual reasoning, and agent interaction. Requirements: Strong experience with data engineering, computer vision, or machine learning infrastructure. Expertise in building and scaling ETL/data pipelines for large unstructured datasets. Proficiency with Python, PyTorch, and distributed data frameworks (e.g., Ray, Spark, Dask). Experience with WebDataset, TFRecords, Parquet, or similar high-throughput data formats. Familiarity with GPU-accelerated preprocessing, NVIDIA DALI, or equivalent systems. Understanding of image/video codecs, data compression, and cloud storage optimization. Preferred Experience: Prior work with simulation-based or synthetic data generation using Unreal Engine, Isaac Sim, or Unity. Experience curating datasets for multimodal or vision-language model training. Knowledge of data ethics, privacy, and compliance frameworks for large-scale AI datasets. Experience contributing to open datasets or data-centric AI research. Why apply: Opportunity to join a fast-growing core team that are already pushing AI breakthroughs Highly competitive salary package Work alongside ambitious and bright superstars from tech and academia Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

Early-stage (vertical RL) company looking to hire a Sr. Applied RS with a strong background in reinforcement learning. Qualifications: Applied Research with MS or PhD in a related field and 4 + years industry experience in deep learning and 2+ years with reinforcement learning Successful track record as a self-starter in 0->1 scenarios with a proven ability to take SOTA models into production Please note: Due to the selective nature of this service and the volume of applicants we typically receive from our job postings, a follow-up email will not be sent until a match is identified with one of the startup investments in our portfolio. About Us: Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: ********************* We are full-time, salaried employees of Greylock who provide free candidate referrals/introductions to our active investments to help them grow/succeed (as one of the many services we provide). Please note: We are not recruiting for any roles within Greylock at this time. This job posting is for direct employment with a startup in our portfolio.

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get in touch!

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

Top investment bank seeking an equity research associate to support a rising senior biotechnology analyst covering mid- and small-cap biotech companies. Responsibilities will include: Candidate should understand that the team is highly motivated to become top-ranked in the biotech industry Conducting proprietary research and evaluating drug pipelines by analyzing scientific literature, attending medical conferences, and consulting industry experts Writing research reports for initiations of coverage, deep dive data analyses, competitive landscaping, and industry/ company news Delving into intellectual property and following patent litigation concerning pharmaceuticals Building and maintaining financial models and powerpoint decks Conceiving and executing on differentiated project ideas Interfacing with company management teams, internal sales and trading personnel, and institutional investors Key Qualifications: 1-2+ years of experience in healthcare investment research required (sell side, buy side, investment banking, etc). Must be fully licensed. Science background required; MD or PhD preferred Motivated to rise in the sell-side industry in the long-term Hard-working, attention to detail, team player Sharp analytical skills in dissecting preclinical and clinical data Deep understanding of, or experience with, drug development and the FDA-approval process for pharmacologic treatments is desirable High proficiency in written/verbal communication Can type >120 words per minute Has experience writing quality sell side reports, producing powerpoints, and creating detailed financial models (e.g. functioning three-statement models, DCFs, market models, etc) Experience building financial models using excel is a plus Primary Location Full Time Salary Range of $100,000 - $120,000.

The Opportunity State-of-the-art technologies that measure multiple cellular aspects of in-vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes. We are looking for an expert in omics data analysis, including deep understanding of cell biology and single cell transcriptomics, and fluent with state-of-the-art analysis techniques. Your expertise will help the team navigate the complexities developing disease relevant cell models and analyzing high throughput phenotypic screens, and ensure that the tools being developed are calibrated and effective, and that analyses are performed to the highest rigor and in line with best practices in the broader scientific community. In this role, you will collaborate closely with experimental biologists and machine learning scientists, support the identification of novel phenotypes, the development of new screening paradigms, and advance our understanding of disease. You will utilize diverse machine learning and bioinformatic methods to perform diverse downstream analyses, including integrating with other data modalities, including imaging and human cohort data in order to extract insights about disease mechanisms. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists that strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. This role will be reporting to the Head of Computational Biology and ML-Omics . This is a hybrid position that requires you to be in our South San Francisco headquarters at least three days per week. You will be joining a vibrant biotech startup that has many opportunities for significant impact. You will work closely with a highly talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients! Responsibilities * Analyze and interpret omics datasets from disease-relevant in-vitro models to identify potential therapeutic targets from perturbation screens * Partner with experimental biologists to design, troubleshoot, and optimize high-throughput experiments and workflows * Integrate insights from multimodal data (bulk/single-cell RNA-seq, microscopy, spatial proteomics, human cohort data) to understand disease mechanisms and generate therapeutic hypotheses * Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions * Communicate findings clearly to cross-functional stakeholders through reports, visualizations, presentations, and publications About You * Ph.D. in computational biology, systems biology, bioengineering, machine learning, or a related discipline, with 3+ years of working experience post graduation * Extensive hands on experience analyzing single-cell and bulk RNA-seq data * Experience working with functional genomic assays data (RNA/ATAC/ChIP-seq, etc) * Experience analyzing data from perturbational screens (e.g. perturb-seq) * An understanding of systems biology, molecular biology, or disease biology (e.g. neurological disorders, metabolic disorders) * Experience with spatial proteomics and/or transcriptomics * Strong programming skills and proficiency with Python scientific packages (i.e., numpy, pandas, scanpy) * Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions * Committed to writing well-commented code and documentation, and familiarity with coding best practices (i.e. version control, code review) * Publication record of meaningful contributions to high-quality work in relevant computational biology, systems biology, life sciences, or biomedical venues Compensation & Benefits at insitro Our target starting salary for successful US-based applicants for this role is $175,000 - $200,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data. This role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies. In addition, insitro also provides our employees: * 401(k) plan with employer matching for contributions * Excellent medical, dental, and vision coverage as well as mental health and well-being support * Open, flexible vacation policy * Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc) * Quarterly budget for books and online courses for self-development * Support to attend professional conferences that are meaningful to your career growth and role's responsibilities * New hire stipend for home office setup * Monthly cell phone & internet stipend * Access to free onsite baristas and cafe with daily lunch and breakfast for employees who are either onsite or hybrid * Access to free onsite fitness center for employees who are either onsite or hybrid * Access to a free commuter bus and ferry network that provides transport to and from our South San Francisco HQ from locations all around the Bay Area insitro is an equal opportunity employer. All applicants will be considered for employment without attention to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran or disability status. We believe diversity, equity, and inclusion need to be at the foundation of our culture. We work hard to bring together diverse teams-grounded in a wide range of expertise and life experiences-and work even harder to ensure those teams thrive in inclusive, growth-oriented environments supported by equitable company and team practices. All candidates can expect equitable treatment, respect, and fairness throughout the interview process. Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com, and if in doubt, contact us at ****************. #LI-Hybrid About insitro insitro is a drug discovery and development company using machine learning (ML) and data at scale to decode biology for transformative medicines. At the core of insitro's approach is the convergence of in-house generated multi-modal cellular data and high-content phenotypic human cohort data. We rely on these data to develop ML-driven, predictive disease models that uncover underlying biologic state and elucidate critical drivers of disease. These powerful models rely on extensive biological and computational infrastructure and allow insitro to advance novel targets and patient biomarkers, design therapeutics and inform clinical strategy. insitro is advancing a wholly owned and partnered pipeline of insights and therapeutics in neuroscience and metabolism. Since launching in 2018, insitro has raised over $700 million from top tech, biotech and crossover investors, and from collaborations with pharmaceutical partners. For more information on insitro, please visit ****************

Quantitative Geneticist, Predictive Breeding Time Type: Full Time The Opportunity At Ohalo, we are building the future of agriculture with our breakthrough Boosted breeding technology. We are seeking a visionary and hands-on Quantitative Geneticist to be a principal architect of the computational engine that drives our entire crop improvement strategy. This isn't a typical modeling role. You will be at the nexus of genetics, data science, and engineering, designing the predictive systems that guide our breeding decisions. You will build and deploy everything from genomic selection models to sophisticated simulations that chart the course of our breeding portfolio. If you are driven to solve complex problems and want to see your code and models directly translate into real-world genetic gain, this is a unique opportunity to make a foundational impact. Responsibilities As a key member of our technical team, your responsibilities will be organized around three core pillars: 1. Core Predictive Science Genomic Prediction & GWAS: Design, build, and validate the primary statistical models (e.g., GBLUP, ss GBLUP, GWAS) that form the foundation of our predictive capabilities, translating genotype and phenotype data into actionable insights. Breeding Simulation: Evolve our in-house breeding simulation platform to run complex, large-scale scenarios. Your models will answer critical strategic questions about resource allocation, risk management, and the optimal path to achieve our breeding objectives. 2. Strategic Decision Modeling Pipeline Optimization: Move beyond prediction to prescription. Design and implement online optimization models (e.g., using multi-armed bandits, online learning, metaheuristics) to create a self-improving system that dynamically allocates resources and maximizes the rate of genetic improvement. Portfolio Management & Utility: Develop and integrate multi-trait utility functions that align our selection strategy with market needs and product profiles. You will help manage the entire breeding portfolio as a strategic asset. 3. Innovation & Collaboration Accelerate Research with AI: Act as a force multiplier by leveraging modern AI tools across the research lifecycle. This includes using LLMs for hypothesis generation, pioneering the use of genomic foundation models (e.g., Evo2), and using AI-assisted tools to write, debug, and document production-quality code. Drive Cross-Functional Impact: Serve as a critical scientific partner to domain experts (breeders, plant scientists), Machine Learning Engineers (MLEs), and Data Engineers (DEs). Proactively translate breeding objectives into modeling requirements and ensure your solutions are seamlessly integrated into our operational workflows. Uphold Statistical Rigor: Collaborate with fellow quantitative scientists to champion statistical integrity across the organization, from experimental design to model validation and interpretation. Candidate Profile Education: M.S. or Ph.D. in Quantitative Genetics, Statistical Genetics, Plant Breeding, Biostatistics, Operations Research, or a related computational field. Core Experience: 2-5+ years of hands-on experience applying quantitative principles in a research or industry setting. A strong portfolio of projects demonstrating the application of predictive modeling and/or simulation is highly desired. Programming Excellence: Expert-level proficiency in Python and its scientific computing stack (e.g., NumPy, SciPy, Pandas, Scikit-learn). Demonstrable experience building modular, testable, and maintainable code is essential. Hands-on experience using generative AI tools (e.g., GitHub Copilot) to accelerate the development of scientific code. Statistical Modeling Expertise: Deep theoretical and practical understanding of mixed models for genetic evaluation (e.g., GBLUP, ss GBLUP). Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. Familiarity with decision theory and online optimization frameworks (e.g., multi-armed bandits, Thompson sampling) for resource allocation. Experience with or interest in applying genomic foundation models (e.g., Evo2, other LLM-like architectures) to learn from large-scale sequence data. Experience with machine learning algorithms (e.g., XGBoost, Ridge Regression) as applied to genomic data. Collaboration & Communication: A proven ability to work effectively in a cross-functional team. You must be able to translate complex technical and scientific concepts for different audiences and work collaboratively to turn models into real-world impact. Genomic Data Acumen: Experience handling and processing large-scale genomic datasets (e.g., SNP arrays, sequencing data) is required. Bonus Points For: Proficiency in R, particularly for reading and translating legacy statistical models (e.g., brms, sommer, ASReml). Experience with workflow management tools (e.g., Nextflow, Snakemake). Familiarity with cloud computing environments (GCP, AWS) and data warehousing technologies (e.g., BigQuery). Knowledge of polyploid genetics and modeling. About Ohalo: Ohalo™ aims to accelerate evolution to unlock nature's potential. Founded in 2019, Ohalo develops novel breeding systems and improved plant varieties that help farmers grow more food with fewer natural resources, increasing the yield, resiliency, and genetic diversity of crops to sustainably feed our population. Ohalo's breakthrough technology, Boosted Breeding™, will usher in a new era of improved productivity to radically transform global agriculture. For more information, visit ************** The anticipated pay range for this role is $125,000 - $150,000 per year for our San Francisco, CA location, though salary will be based on a variety of factors including, but not limited to, experience, skills, education, and location. Notes: If you previously applied for a job at Ohalo, we encourage you to restate your interest in the position by submitting your application. No visa sponsorship is available for this position at this time. No recruiters please.

The Department of Biological Sciences at San José State University invites applications for an Assistant, Associate, or Full Professor in the area of Clinical Laboratory Science. We are a team of dedicated teacher-scholars recognized for our commitment to excellent teaching, engaging students in research projects, and promoting equity, diversity, and inclusion in CLS, Biology, and in STEM disciplines. The incumbent will serve as Director for both the Clinical Laboratory Scientist (CLS) Training Program and the Clinical Genetic Molecular Biologist Scientist (CGMBS) Training Program, and will be expected to teach in these programs in their area of specialty. The Department of Biological Sciences offers degrees in Microbiology, Molecular Biology, Ecology and Evolution, Systems Physiology, General Biology, Marine Biology, and is the home department for both the Clinical Laboratory Scientist (CLS) Training Program and the Clinical Genetic Molecular Biologist Scientist (CGMBS) Training Program. There are approximately 1000 undergraduate majors, 65 Master's students enrolled in Biology, 59 CLS students, and 16 CGMBS students enrolled. Facilities include: a new, state of the art Interdisciplinary Science Building, molecular and microbiology research and teaching labs (BSL2 capable); imaging with confocal laser microscope (Zeiss 700), flow cytometry (FACSCalibur & FACScan); cell culture; Proteomics (QTOF LC/MS/MS, 2D Gel, TYPHOON Imager, and AKTA FPLC systems); anatomy and physiology research and teaching labs; bioinformatics and general computing labs; greenhouses, herbarium, plant growth chambers, and museums. There is technical support for laboratory courses and equipment maintenance. Opportunities for collaboration with biotechnology companies and local research-intensive universities are supported. The Department of Biological Sciences and San José State University value diversity, equity, inclusion, and belonging. Our excellence in research, teaching, and service can only be fully realized by faculty, students, and staff who share our commitment to these values. SJSU enrolls more than 36,000 students, many of whom are historically underserved, and around 45% are first-generation and 38% are Pell-recipients. SJSU is a Hispanic Serving Institution (HSI) and Asian American and Native American Pacific Islander (AANAPISI) Serving Institution. The university's commitment to social justice extends from its vibrant, inclusive campus to an international network of over 275,000 alumni. As such, San José State is committed to increasing the diversity of its faculty so our disciplines, students, and the community can benefit from multiple ethnic and gender perspectives. Successful candidates will demonstrate evidence of a commitment to equity and inclusion through their research, teaching, and/or service. We invite all applicants to include a Statement of Inclusive Excellence (or incorporate it into your cover letter) to share how your lived and professional experiences will contribute to the SJSU community-particularly in relation to student success and inclusive education. A guide to writing this statement can be found at SJSU Inclusive Excellence Statement Guidelines. Required Qualifications Insert required qualifications here. Includes terminal degree requirement and other qualification items. Be specific and clear, carefully considering how these qualifications contribute to student success and how candidates will demonstrate these in their application materials and interviews. Please note that hire decisions must be based primarily on the items denoted as required. Fewer, broader required qualifications lead to more diverse applicant pools. * Doctoral degree in education, microbiology, or a related field. M.S. in biology or a related field may be considered with appropriate experience. * Current CA CLS Generalist license * Current (ASCP or ASCPi) Generalist certification as a medical laboratory scientist * Three years of teaching experience * Knowledge of education methods and administration as well as current NAACLS accreditation procedures and certification procedures * Applicants must demonstrate an awareness of and sensitivity to the educational goals of a socially and economically diverse student population as might have been gained in cross-cultural study, training, teaching, and other comparable experience. Preferred Qualifications Priority will be given to candidates who possess one or more of the following: * Expertise or teaching experience in one or more of the following: Hematology, Medical Microbiology, or Immunology * Five years of practical experience in clinical laboratory work * Management/supervisory experience leading and supervising personnel and projects * Budgeting/fiscal experience Key Responsibilities * The successful candidate is expected to manage the operations of the CLS and CGMBS programs, including budget and fiscal activities, evaluation of applications, academic personnel, recruitment of teaching staff, facility coordination, promotion of the program, and curriculum planning and development. * The candidate will ensure accreditation, licensing, safety and risk management requirements are met, update changes in standards for accreditation, and track all required statistics annually for accreditation purposes. * Teaching duties may include hematology, medical microbiology, or immunology modules in the CLS/CGMBS curriculum. * The candidate will participate in shared governance, usually in department, college, and university committees and other service assignments. * The candidate must demonstrate awareness and experience understanding the needs of a student population of great diversity - in age, abilities, cultural background, ethnicity, religion, economic background, primary language, sexual orientation, gender identity, and academic preparation - through inclusive course materials, teaching strategies and advisement. Other Duties Note that all San José State University employees are considered mandated reporters under the California Child Abuse and Neglect Reporting Act and are required to comply with the requirements set forth in CSU Executive Order 1083 as a condition of employment. Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act (Clery Act) and CSU systemwide policy, some faculty duties may lead to designation as a Campus Security Authority (CSA). CSAs are required to complete Clery Act training and to immediately report Clery incidents to the institution. Faculty employees must complete CSU employee training as assigned and required based on their role (e.g., Data Security, FERPA, Preventing Discrimination and Harassment, Title IX, Health and Safety). The President may recommend or require compliance with safety measures that decrease the likelihood of COVID-19 transmission or illness and allows the core mission and activities of the campus to continue. Application Procedure Select Apply Now to complete the SJSU Online Employment Application and attach the following documents: * letter of interest * curriculum vitae * Optional statement of inclusive excellence (limit two pages) * Statement of teaching interests/philosophy (limit 2 pages) that describes the applicant's pedagogical approach, teaching experiences, and their view of the role of faculty in student success * Names and contact information for three references who are willing to provide letters of reference upon request. Inquiries may be directed to the Department Chair or Search Committee Chair: Dr. Rachael French (***********************) Conditional Offer The work for this faculty position is located in the State of California and requires commuting to the campus Employment is contingent upon US residence and proof of eligibility to work in the United States. Satisfactory completion of a background check (including a criminal records check) is required for employment. SJSU will make a conditional offer of employment, which may be rescinded if the background check reveals disqualifying information, and/or it is discovered that the candidate knowingly withheld or falsified information. Failure to satisfactorily complete the background check may affect the continued employment of a current employee who was conditionally offered the position. San José State University: Silicon Valley's Public University Located in the heart of Silicon Valley - one of the most innovative regions in the world - San José State University is the founding campus of the 23-campus California State University (CSU) system and the first public university in the West. Recognized as a leading transformative educational institution, San José State is an essential partner in the technological, economic, cultural, and social development of Silicon Valley, the Bay Area, and California. SJSU is a top-200 school nationally in research funding and second highest in research productivity in the CSU system. Cutting-edge research, world-class scholarship, student-centered learning, diverse communities, and commitment to social justice, allow SJSU to provide life-changing opportunities and advance the public good locally and globally. Equal Employment Statement San José State University prohibits discrimination on the basis of Age, Ancestry, Caste, Color, Disability, Ethnicity, Gender, Gender Expression, Gender Identity, Genetic Information, Marital Status, Medical Condition, Military Status, Nationality, Race, Religion, Religious Creed, Sex, Sexual Orientation, Sex Stereotype, and Veteran Status. This policy applies to all San José State University students, faculty, and staff as well as University programs and activities. Reasonable accommodations are made for applicants with disabilities who self-disclose. Campus Security and Fire Safety Notification Pursuant to the Jeanne Clery Disclosure of Campus Security Policy and Campus Crime Statistics Act, the Annual Security Report (ASR) is also now available for viewing at **************************************************************** The ASR contains the current security and safety-related policy statements, emergency preparedness and evacuation information, crime prevention and Sexual Assault prevention information, and information about drug and alcohol prevention programming. The ASR also contains statistics of Clery crimes for San José State University locations for the three most recent calendar years. A paper copy of the ASR is available upon request by contacting the Office of the Clery Director by phone at ************ or by email at ************************. Pursuant to the Higher Education Opportunity Act, the Annual Fire Safety Report (AFSR) is available at ******************************************************************* The purpose of this report is to disclose statistics for fires that occurred within SJSU on-campus housing facilities for the three most recent calendar years, and to distribute fire safety policies and procedures intended to promote safety on Campus. A paper copy of the AFSR is available upon request by contacting the Housing Office by phone at ************ or by email at **********************. Advertised: Aug 25 2025 Pacific Daylight Time Applications close:

The Division of Medical Genetics in the Department of Pediatrics at Stanford University seeks a board certified/ eligible Medical Geneticist to join the Department and Division as an Assistant Professor, Associate Professor or Professor in the University Medical Line or as a Clinician Educator. Candidates must hold an MD or equivalent degree with board eligibility or board certification in medical genetics and genomics and have medical licensure in California by starting date. The major criteria for appointment for faculty in the University Medical Line shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill. The major criterion for appointment as Clinician Educators is excellence in the overall mix of clinical care, teaching, administrative and/or scholarship appropriate to the programmatic need the individual is expected to fulfill. Faculty/Academic rank and line will be determined by the qualifications and experience of the successful candidate. We expect the successful candidate to participate in the care of patients under the care of the medical genetics service, biochemical genetics service and the perinatal genetics service. The candidate will be involved in formal and informal teaching of Medical Genetics residents, residents and fellows in other specialties, medical students and other graduate students. To be considered a candidate in the University Medical Line the successful candidate must have a focused research interest and a record or potential of scholarly accomplishment. For candidates holding certification in a specialty in addition to medical genetics, a secondary appointment in an additional Department may be possible. The activities of the Division/Department are diverse and include participation in the education of medical students, medical genetics residents and students in the Masters of Human Genetics and Genetic Counseling Program. Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from all who would bring additional dimensions to the University's research, teaching and clinical missions. Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact disability.access@stanford.edu . The university's central functions of research and education depend on freedom of thought, and expression. The Department of Pediatrics, School of Medicine, and Stanford University value faculty who will help foster an open and respectful academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and perspectives. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these values. How to apply: Please submit a CV and cover letter with an optional discussion of how your work and experience fosters additional dimensions to the university's mission and values. For questions, please contact: Dr. Michael Rosen, MD, MSCI, Search Chair c/o Stephanie Martinez (email: *********************) The expected base pay range for this position is: Assistant Professor Rank: $214,000-$227,000 Associate Professor Rank: $245,000-$258,000 Professor Rank: $291,000-$321,000 This pay range reflects base pay, which is based on faculty rank and years in rank. It does not include all components of the School of Medicine's faculty compensation program or pay from participation in departmental incentive compensation programs. For more information about compensation and our wide-range of benefits, including housing assistance, please contact the hiring department. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

Series A company looking to hire a Sr. Applied RS with a good background in multi-agent reinforcement learning. The related challenge is figuring out how to use feedback from an objective function on (consumer) pricing to reinforce a multi-agent enterprise system (many components). Qualifications: Applied Research with MS or PhD in a technical field and 4 + years relevant industry experience Successful track record as a self-starter in 0->1 scenarios with a proven ability to take SOTA models into production Please note: Due to the selective nature of this service and the volume of applicants we typically receive from our job postings, a follow-up email will not be sent until a match is identified with one of the startup investments in our portfolio. About Us: Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: ********************* We are full-time, salaried employees of Greylock who provide free candidate referrals/introductions to our active investments to help them grow/succeed (as one of the many services we provide).

⚡ Research Scientist - Data focus 💊 Foundation Models, AI Research Institute 🌎 San Francisco Bay Area, USA 💸 $200,000 - $350,000 salary + bonus Come join a revolutionary AI research lab in SF Bay Area that is poised to develop & publish high-impact breakthroughs in GenAI - across LLMs and Multimodal AI. As part of the team, you'll work at the intersection of data, large-scale training, and foundation model innovation. You will collaborate with world-class researchers, data scientists, and engineers to solve critical challenges in creating robust, scalable, and reasoning-capable LLMs. Your research will shape the way data is curated, processed, and leveraged to train the next generation of intelligent systems. Responsibilities: Lead research on data-centric approaches for LLMs, including pretraining corpus design, data valuation, and speculative decoding strategies. Develop pipelines to process challenging data sources into structured and reproducible training datasets. Build and optimize agentic data pipelines, integrating retrieval, self-curation, and multi-agent feedback for high-quality training and evaluation data. Collaborate with researchers on alignment and reasoning-focused training that leverage data-driven approaches for improving LLM capabilities. Prototype and deploy evaluation frameworks to measure data quality, coverage, and downstream impact on LLM reasoning. Publish findings at top-tier venues (e.g., NeurIPS, ICLR, ACL, EMNLP) and represent the institute at international conferences. Contribute to open-source tools, datasets, and benchmarks that advance the global foundation model research community. Requirements: Master's degree in Computer Science, Data Science, or a related technical field (PhD strongly preferred) Experience collecting and curating high-quality text data including multi-lingual data. Hands-on experience with large-scale dataset curation and preprocessing for ML/LLM training. Prior works synthesizing complex datasets. Code, math, and agentic data are higher priority Experience with ML infrastructure for scalable training, evaluation, and debugging. Experience at the intersection of data and post-training (RL/SFT) Proven ability to independently drive research questions related to data quality, scaling, or reasoning. Preferred Experience: Experience with retrieval-augmented generation (RAG), agentic data pipelines, or reasoning benchmarks. Contributions to speculative decoding, self-curation, or reinforcement learning from synthetic data. Background in knowledge graphs, semantic search, or indexing systems. Strong publication record in leading AI conferences. Prior contributions to open-source ML data tools or benchmarks. Prior work on speculative decoding/contributions to LLM serving engines Prior work on training LLM-as-a-judge Deep expertise with tokenization/training tokenizers Why apply: Opportunity to build out a new division at the forefront of AI innovation FAANG competitive salary & package Work alongside superstars from FAANG labs & leading AI companies Medical, Dental and Vision Insurance Relocation package available 🌎 San Francisco Bay Area, USA 📧 Interested in applying? Please click on the ‘Easy Apply' button or alternatively email me your resume at ************************

SUPERCOMPUTING AI LAB W/ MULTIMODAL GENERAL AGENT AI STARTUP - SERIES A $1.2B VALUATION Goliath Partners has exclusively teamed up with an early stage startup AI Lab in SF currently valued at over $1B just after announcing their Series A. The firm has fundamental research bets on next-gen model architectures for long term memory and continual learning. Have lots of GPUs and are planning to get to frontier soon on the model side. Funding wise, their Series A was led by none other than Jann Tallinn. Jann has only led two other Series A's in the past - DeepMind and Anthropic! The team includes ex-DeepMind, Nvidia, Anthropic and Twitter professionals, and they are operating at the cutting edge of the AI space. They're hiring an ML Research Engineer to: Design and implement autonomous agents that can code, reason, and self-verify across real software environments Build full-stack infrastructure for prompt routing, task planning, retrieval, and sandboxed execution Apply post-training techniques (SFT, DPO, RLHF) and build eval benchmarks for multi-step reasoning and coding tasks Total Comp: $300-325k from a base perspective. Equity will also be involved at anywhere from .1% - 1% (equaling $1-10M in equity). If this sounds interesting, I'd love to share more. Please apply with an updated copy of your resume and Goliath will get in touch!

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.

Job Description Quantitative Geneticist, Predictive Breeding Time Type: Full Time The Opportunity At Ohalo, we are building the future of agriculture with our breakthrough Boosted breeding technology. We are seeking a visionary and hands-on Quantitative Geneticist to be a principal architect of the computational engine that drives our entire crop improvement strategy. This isn't a typical modeling role. You will be at the nexus of genetics, data science, and engineering, designing the predictive systems that guide our breeding decisions. You will build and deploy everything from genomic selection models to sophisticated simulations that chart the course of our breeding portfolio. If you are driven to solve complex problems and want to see your code and models directly translate into real-world genetic gain, this is a unique opportunity to make a foundational impact. Responsibilities As a key member of our technical team, your responsibilities will be organized around three core pillars: 1. Core Predictive Science Genomic Prediction & GWAS: Design, build, and validate the primary statistical models (e.g., GBLUP, ss GBLUP, GWAS) that form the foundation of our predictive capabilities, translating genotype and phenotype data into actionable insights. Breeding Simulation: Evolve our in-house breeding simulation platform to run complex, large-scale scenarios. Your models will answer critical strategic questions about resource allocation, risk management, and the optimal path to achieve our breeding objectives. 2. Strategic Decision Modeling Pipeline Optimization: Move beyond prediction to prescription. Design and implement online optimization models (e.g., using multi-armed bandits, online learning, metaheuristics) to create a self-improving system that dynamically allocates resources and maximizes the rate of genetic improvement. Portfolio Management & Utility: Develop and integrate multi-trait utility functions that align our selection strategy with market needs and product profiles. You will help manage the entire breeding portfolio as a strategic asset. 3. Innovation & Collaboration Accelerate Research with AI: Act as a force multiplier by leveraging modern AI tools across the research lifecycle. This includes using LLMs for hypothesis generation, pioneering the use of genomic foundation models (e.g., Evo2), and using AI-assisted tools to write, debug, and document production-quality code. Drive Cross-Functional Impact: Serve as a critical scientific partner to domain experts (breeders, plant scientists), Machine Learning Engineers (MLEs), and Data Engineers (DEs). Proactively translate breeding objectives into modeling requirements and ensure your solutions are seamlessly integrated into our operational workflows. Uphold Statistical Rigor: Collaborate with fellow quantitative scientists to champion statistical integrity across the organization, from experimental design to model validation and interpretation. Candidate Profile Education: M.S. or Ph.D. in Quantitative Genetics, Statistical Genetics, Plant Breeding, Biostatistics, Operations Research, or a related computational field. Core Experience: 2-5+ years of hands-on experience applying quantitative principles in a research or industry setting. A strong portfolio of projects demonstrating the application of predictive modeling and/or simulation is highly desired. Programming Excellence: Expert-level proficiency in Python and its scientific computing stack (e.g., NumPy, SciPy, Pandas, Scikit-learn). Demonstrable experience building modular, testable, and maintainable code is essential. Hands-on experience using generative AI tools (e.g., GitHub Copilot) to accelerate the development of scientific code. Statistical Modeling Expertise: Deep theoretical and practical understanding of mixed models for genetic evaluation (e.g., GBLUP, ss GBLUP). Proven experience with Bayesian statistics, applying methods such as Bayesian GBLUP, hierarchical models, and clustering using MCMC or variational inference. Familiarity with decision theory and online optimization frameworks (e.g., multi-armed bandits, Thompson sampling) for resource allocation. Experience with or interest in applying genomic foundation models (e.g., Evo2, other LLM-like architectures) to learn from large-scale sequence data. Experience with machine learning algorithms (e.g., XGBoost, Ridge Regression) as applied to genomic data. Collaboration & Communication: A proven ability to work effectively in a cross-functional team. You must be able to translate complex technical and scientific concepts for different audiences and work collaboratively to turn models into real-world impact. Genomic Data Acumen: Experience handling and processing large-scale genomic datasets (e.g., SNP arrays, sequencing data) is required. Bonus Points For: Proficiency in R, particularly for reading and translating legacy statistical models (e.g., brms, sommer, ASReml). Experience with workflow management tools (e.g., Nextflow, Snakemake). Familiarity with cloud computing environments (GCP, AWS) and data warehousing technologies (e.g., BigQuery). Knowledge of polyploid genetics and modeling. About Ohalo: Ohalo™ aims to accelerate evolution to unlock nature's potential. Founded in 2019, Ohalo develops novel breeding systems and improved plant varieties that help farmers grow more food with fewer natural resources, increasing the yield, resiliency, and genetic diversity of crops to sustainably feed our population. Ohalo's breakthrough technology, Boosted Breeding™, will usher in a new era of improved productivity to radically transform global agriculture. For more information, visit ************** The anticipated pay range for this role is $125,000 - $150,000 per year for our San Francisco, CA location, though salary will be based on a variety of factors including, but not limited to, experience, skills, education, and location. Notes: If you previously applied for a job at Ohalo, we encourage you to restate your interest in the position by submitting your application. No visa sponsorship is available for this position at this time. No recruiters please.

The Division of Medical Genetics in the Department of Pediatrics at Stanford University seeks a board certified/ eligible Medical Geneticist to join the Department and Division as an Assistant Professor, Associate Professor or Professor in the University Medical Line or as a Clinician Educator. Candidates must hold an MD or equivalent degree with board eligibility or board certification in medical genetics and genomics and have medical licensure in California by starting date. + The major criteria for appointment for faculty in the **University Medical Line** shall be excellence in the overall mix of clinical care, clinical teaching, scholarly activity that advances clinical medicine, and institutional service appropriate to the programmatic need the individual is expected to fulfill. + The major criterion for appointment as **Clinician Educators** is excellence in the overall mix of clinical care, teaching, administrative and/or scholarship appropriate to the programmatic need the individual is expected to fulfill. Faculty/Academic rank and line will be determined by the qualifications and experience of the successful candidate. We expect the successful candidate to participate in the care of patients under the care of the medical genetics service, biochemical genetics service and the perinatal genetics service. The candidate will be involved in formal and informal teaching of Medical Genetics residents, residents and fellows in other specialties, medical students and other graduate students. To be considered a candidate in the University Medical Line the successful candidate must have a focused research interest and a record or potential of scholarly accomplishment. For candidates holding certification in a specialty in addition to medical genetics, a secondary appointment in an additional Department may be possible. The activities of the Division/Department are diverse and include participation in the education of medical students, medical genetics residents and students in the Masters of Human Genetics and Genetic Counseling Program. _Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law. Stanford also welcomes applications from all who would bring additional dimensions to the University's research, teaching and clinical missions._ _Consistent with its obligations under the law, the University will provide reasonable accommodations to applicants and employees with disabilities. Applicants requiring a reasonable accommodation for any part of the application or hiring process should contact_ _disability.access@stanford.edu_ _._ _The university's central functions of research and education depend on freedom of thought, and expression. The Department of Pediatrics, School of Medicine, and Stanford University value faculty who will help foster an open and respectful academic environment for colleagues, students, and staff with a wide range of backgrounds, identities, and perspectives. Candidates may choose to include as part of their research and teaching statements a brief discussion about how their work and experience will further these values._ **How to apply:** Please submit a CV and cover letter with an optional discussion of how your work and experience fosters additional dimensions to the university's mission and values. **For questions, please contact:** Dr. Michael Rosen, MD, MSCI, Search Chair c/o Stephanie Martinez (email: *********************) _The expected base pay range for this position is:_ _Assistant Professor Rank: $214,000-$227,000_ _Associate Professor Rank: $245,000-$258,000_ _Professor Rank: $291,000-$321,000_ This pay range reflects base pay, which is based on faculty rank and years in rank. It does not include all components of the School of Medicine's faculty compensation program or pay from participation in departmental incentive compensation programs. For more information about compensation and our wide-range of benefits (***************************************************** , including housing assistance (************************** , please contact the hiring department. Stanford University has provided a pay range representing its good faith estimate of what the university reasonably expects to pay for the position. The pay offered to the selected candidate will be determined based on factors including (but not limited to) the experience and qualifications of the selected candidate including equivalent years in rank, training, and field or discipline; internal equity; and external market pay for comparable jobs.

Join a Leading Applied Research Lab Pushing the Boundaries of Reinforcement Learning Are you passionate about advancing the frontiers of reinforcement learning (RL)? An innovative AI research lab is seeking talented and ambitious scientists to shape the next generation of RL techniques-especially where they intersect with large models and environment generation. About the Role As an AI Research Scientist focused on RL, you will: Develop novel optimization-based methods for automated RL environment generation Establish baselines for evaluating the quality and diversity of RL environments Design infrastructure to create dynamic environments from historical datasets and agent evaluations Drive your own research agenda, contributing directly to the progress of our platform and the broader AI community What We're Looking For PhD (or equivalent experience) in machine learning, computer science or a related field Strong publication record and/or evidence of research impact (open source, deployed systems, etc.) Deep expertise in reinforcement learning and machine learning fundamentals Proficient in Python and at least one modern ML framework (such as PyTorch or JAX) Bonus Points Experience with post-training large language models (LLMs) Demonstrated software engineering skills Ability to communicate research findings effectively to both technical and non-technical audiences

Amber Bio is a biotechnology company pioneering new gene editing modalities using multi-kilobase edits to reach previously undruggable patient populations. Founded by pioneers in the CRISPR field from leading institutions for gene editing research, the company is developing a first-of-its-kind RNA editing platform that can correct thousands of bases at once, thereby correcting genetic mutations safely and reversibly. If you are interested in building a new frontier in genetic medicine, we welcome you to apply. Job Description: High-Throughput Screening Research Associate II, III (Biodesigner II, III) Responsibilities: Perform massively parallel reporter assays and high-throughput screens across diverse cellular contexts using cellular and molecular readouts. Develop and execute molecular biology workflows such as vector design and cloning, DNA/RNA extraction, RT-PCR, qPCR, and next-generation sequencing. Support cell culture activities and experiments in multiple cell lines, at small and large scales. Design and execute cell-based assays (AAV/lentiviral transduction, transfection, flow cytometry, immunostaining, and other plate reader assays). Engineer and characterize cell-based systems using synthetic biology tools and techniques. Conduct and troubleshoot experiments, independently and in collaboration with colleagues, to optimize screening throughput, sensitivity, and specificity. Proactively troubleshoot technical issues and recommend potential corrective actions based on personal observations and literature searches. Prepare summaries of data and present internally to colleagues and management. Draft SOPs, follow protocols, diligently document experimental data in lab notebooks, and organize and maintain electronic work records. Author scientific reports and data summaries. Collaborate with cross-functional teams to meet project goals, bridging early discovery with high-throughput screens to nominate and optimize candidates for further characterization. Qualifications: Bachelor's or Master's degree in Biology, Biochemistry, Chemical Engineering, Biological Engineering, or a related field. At least 2 years of industry wet lab experience. Mammalian cell culture experience (culturing, transfecting and transducing cells, and DNA/RNA purification from cells). Molecular biology expertise (vector design and cloning, qPCR, primer and probe design, DNA/RNA extraction workflows) Critical thinker with excellent communication skills who thrives in a multidisciplinary, fast-paced team environment. Strong written and verbal communication skills. Preference will be given to those who display: High throughput screening assay development in an industry setting. High motivation, with a strong work ethic and dedication to generating impact. Attention to detail, with the ability to extract deep insights from data. First-principles thinking, and an ability to refine one's intuition based on additional data. Ability to go from ideation to data in an independent fashion. Long-term personal vision with defined career goals. High EQ with team-oriented thinking. Experience with pooled, high-throughput screens using next-generation sequencing-based readouts, and/or preparing screening plasmid libraries from synthesized oligo arrays. Experience with CRISPR-Cas systems and/or gene editing and delivery technologies. Experience preparing next-generation sequencing libraries (Illumina, PacBio, and/or Nanopore platforms). If you have a passion for advancing gene editing technologies and desire to be part of a pioneering biotech company, we encourage you to apply and join our ambitious team. Please apply directly through LinkedIn. Amber Bio is an equal-opportunity employer and encourages applications from candidates of diverse backgrounds. We value diversity and are committed to creating an inclusive and supportive work environment for all employees.