Research fellow jobs in Cupertino, CA

⚡ 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 ************************

Title: AI Research Scientist Responsibilities: Design, execute, and analyze machine learning experiments, establishing strong baselines and selecting appropriate evaluation metrics. Stay up to date with the latest AI research; identify, adapt, and validate novel techniques for company-specific use cases. Define rigorous evaluation protocols, including offline metrics, user studies, and adversarial (red team) testing to ensure statistical soundness. Specify data and annotation requirements; develop annotation guidelines and oversee quality control processes. Collaborate closely with domain experts, product managers, and engineering teams to refine problem statements and operational constraints. Develop reusable research assets such as datasets, modular code components, evaluation suites, and comprehensive documentation. Work alongside ML Engineers to optimize training and inference pipelines, ensuring seamless integration into production systems. Contribute to academic publications and represent the company in research communities, as needed. Educational Qualifications: Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field is strongly preferred. Candidates with a master's degree and exceptional research or industry experience will also be considered. Industry Experience: 3-5 years of experience in AI/ML research roles, ideally in applied or product-focused environments. Demonstrated success in delivering research-driven solutions that have been deployed in production. Experience collaborating in cross-functional teams across research, engineering, and product. Publications in top-tier AI/ML conferences (e.g., NeurIPS, ICML, ACL, CVPR) are a plus. Technical Skills: Strong foundational knowledge in machine learning and deep learning algorithms. Hands-on experience with PEFT/LoRA, adapters, fine-tuning techniques, and RLHF/RLAIF (e.g., PPO, DPO, GRPO). Ability to read, implement, and adapt state-of-the-art research papers to real-world use cases. Proficiency in hypothesis-driven experimentation, ablation studies, and statistically sound evaluations. Advanced programming skills in Python (preferred), C++, or Java. Experience with deep learning frameworks such as PyTorch, Hugging Face, NumPy, etc. Strong mathematical foundations in probability, linear algebra, and calculus. Domain expertise in one or more areas: natural language processing (NLP), symbolic reasoning, speech processing, etc. Ability to translate research insights into roadmaps, technical specifications, and product improvements. AI Research Scientist | Machine Learning | Deep Learning | Natural Language Processing | LLM | Hybrid | San Jose, CA

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).

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.

About our team: Our team is dedicated to revolutionizing B2B e-commerce through the development of a groundbreaking AI search product. Leveraging cutting-edge LLM technology, we're creating a brand new AI search engine and streamline the entire purchasing process for B2B customers. Responsibilities ● Deliver full projects by defining the data structure, framework, design, and evaluation metrics for AI solution development and implementation. ● Develop and deploy Large Language Models (LLMs) to empower search and agent systems for a variety of applications. ● Identify new and upcoming product innovation areas by interacting with potential external and internal collaborators. ● Identify undefined problems in existing technology and engage stakeholders and leaders to address them. Qualifications ● PhD, Master's, or Bachelor's degree in Computer Science, Engineering, Mathematics, or related fields. ● Ability to implement and verify state-of-the-art NLP or Computer Vision algorithms. ● Experience in successfully applying machine learning approaches to real-world personalization problems. ● Experience with building large language models. ● Knowledge of statistical methods, with strong mathematical skills. ● Excellent problem-solving and programming skills in Python. The pay range for this position at commencement of employment is expected to be between $196,500/year and $325,500/year. However, base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If hired, employee will be in an “at-will position” and the Company reserves the right to modify base salary (as well as any other discretionary payment or compensation program) at any time, including for reasons related to individual performance, Company or individual department/team performance, and market factors.

Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging artists to global brands-everything they need to design and deliver exceptional digital experiences! We're passionate about empowering people to create beautiful and powerful images, videos, and apps, and transform how companies interact with customers across every screen. We're on a mission to hire the very best and are committed to creating exceptional employee experiences where everyone is respected and has access to equal opportunity. We realize that new ideas can come from everywhere in the organization, and we know the next big idea could be yours! The Opportunity Reporting directly to the Director of the Digital Experience Marketing and Integrated GTM Strategy, this role will drive high-impact marketing initiatives that leverage agentic capabilities to align Adobe's enterprise go-to-market (GTM) strategy with customer needs, sales plays, and product innovation. The ideal candidate will bring a strong mix of strategic thinking, cross-functional leadership, and operational rigor to drive measurable business outcomes across the funnel. What You'll Do You'll work cross-functionally to drive strategic initiatives that span AI-assisted Marketing Capabilities, Integrated GTM Strategy & Alignment, and Translating Account, Persona & Content Strategy into Actionable Insights, Vision-setting and Storytelling. This is a high-visibility role with exposure to senior leadership and opportunities to shape how Adobe delivers experiences to enterprise customers. Key contributions: * Develop AI-Driven Marketing Capabilities: Collaborate on initiatives to develop agentic capabilities for Business Development Reps and Marketers; scoping use cases and translating data into actionable insights and next-best-action recommendations. Support Proof-of-Concept testing to improve agentic capabilities and recommendations. * Foster Integrated GTM Strategy & Alignment: Support the development of strategies to deliver unified customers experiences by synthesizing data from multiple sources (CRM, web, campaign, sales). Partner with Product Marketing, Sales Strategy, and Analytics to shape our unified approach to customers and ensure alignment with sales plays, product priorities, and customer personas. * Translate Account, Persona, & Content Strategy and Actionable Insights: Contribute to the creation and evolution of marketing scorecards and dashboards (e.g., Power BI, CJA B2B), helping teams translate data into actionable insights to inform GTM prioritization. Assist in building and maintaining dashboards, heatmaps, and prioritization tools to support targeted engagement strategies. * Cross-Functional Leadership: Lead cross-functional workstreams with stakeholders across Enterprise Marketing, PMM, Sales, Content Strategy, ACS, and DX Products to drive alignment and execution. Experience We're seeking a highly analytical and strategic thinker to join our Integrated GTM Strategy & PMO team. This role is ideal for someone with a strong foundation in marketing, data analytics, decision sciences, or strategy consulting, and a passion for driving business impact through customer-centric, data-informed marketing strategies. * Currently enrolled in a full-time MBA program graduating between December 2025 - June 2026 * Exceptional analytical and quantitative problem solving skills, including conducting research, analyzing data, developing hypotheses, and synthesizing recommendations * Exceptional written and verbal communication skills with the ability to influence both peers and leaders * Experience in B2B marketing, GTM strategy, or marketing operations preferred * Proven ability to lead cross-functional initiatives and influence senior stakeholders. * Familiarity with AI-powered marketing tools, CRM systems (e.g., Salesforce), and campaign orchestration platforms preferred * Excellent communication and storytelling skills, with a track record of translating complex data into compelling narratives. Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this position is $84,300 -- $163,400 annually. Pay within this range varies by work location and may also depend on job-related knowledge, skills, and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP). In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award. State-Specific Notices: California: Fair Chance Ordinances Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances. Colorado: Application Window Notice Dec 31 2025 12:00 AM If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs. Massachusetts: Massachusetts Legal Notice It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability. Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other applicable characteristics protected by law. Learn more. Adobe aims to make Adobe.com accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com or call **************.

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.

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

⚡ 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 ************************

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.

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.

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.