Research fellow jobs in Petaluma, 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

We're working with a San Francisco client that's got a research team of 50~ professionals and looking to further expand it. They are specifically looking to flesh out their Research Group by hiring a Research Scientist on a hybrid basis. They have seen $300M in a recent fund raise. Skills targeted: PhD in Physics/ Quantum Physics/ Theory/ Statistics/ Mathematics/ Computational Science or similarly related field. 2+ YoE working with AI Agents. Good exposure to LLMs. Ideally a background in Audio focused research. Alternatively Search, would also be highly advantageous. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

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 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 ************************

The University of California, San Francisco (UCSF) is dedicated to advancing health worldwide through innovative research, high-quality education, and exceptional patient care. UCSF is recognized for fostering collaboration among its renowned graduate schools, medical center, and research programs. The university is committed to excellence, driving breakthroughs that improve lives. UCSF serves as a hub for scientific discovery and education in the heart of San Francisco, CA. The position is in the group of Drs. Boris Bastian and Iwei Yeh at UCSF's Helen Diller Family Comprehensive Cancer Center, leaders in melanoma genetics and translational research. The lab offers a stimulating, collaborative environment with access to cutting-edge technologies and interdisciplinary expertise. Role Description This is a full-time, on-site role for a Postdoctoral Researcher based in the Melanoma Discovery Lab at the University of California, San Francisco (UCSF) is seeking a highly motivated postdoctoral fellow (MD or PhD) to study systemic immune responses to gene fusion-driven cancers. This project explores how potent oncogenic fusions can initiate neoplastic growth while simultaneously triggering immune surveillance, with Spitz tumors serving as a model. The broader aim is to understand how similar transient, immune-contained lesions may arise in other tissues and be eliminated before clinical detection. The fellow will join a collaborative effort between cancer geneticists/melanoma biologists and genetic immunologists, combining genomic and immunologic approaches to study the systemic response to fusion-driven neoplasms. Qualifications MD or PhD in cancer biology, immunology, genetics, or related fields Strong research background and publication record Experience with molecular, genomic, or immunologic methods preferred Intellectual curiosity about tumor-immune system interactions Proficiency in Laboratory Skills and experience in conducting hands-on experimental work Strong Research and Data Analysis capabilities with attention to detail Experience with publication in peer-reviewed journals is a plus To Apply Send a CV, brief statement of research interests, and contact information for three references to **********************.

Clinical Research Investigator (MD/DO) DM Clinical Research, the largest privately-owned research management organization in the Houston area and one of the top 50 in the country, is looking for an Investigator for our site in San Francisco, CA. This individual will conduct all clinical trials (studies) according to ICH, GCP, local regulations, study protocols, and company processes. Responsibilities Ensures the medical well-being and safety of the participants through the safe performance and execution of the studies. Assists in maintaining clinical oversight and quality on the studies registered on and delivers on study targets, thereby contributing to the commercial success of the site. Reviews enrollment progress, pre-screening and screening success rates, screen failure rates, safety, and retention of participants. Interprets protocols and IB and participates in initiatives to strategize for patient recruitment. Carries out clinical evaluation and assessment of participants to ensure eligibility to enroll in studies. Ensures and protects the welfare and safety of participants through ethical conduct. Fulfills and complies with all medical duties as per protocol, SOP/COP and ICH GCP and local regulations. Exercises meticulous attention to detail in documentation and patient care. Requirements Medical license (MD, DO) - California 2 years experience as a Clinical Research Investigator (Principal Investigator or Sub-Investigator) Bilingual Spanish a plus Flexible hours - schedule can be tailored as required.

Thinking Machines Lab's mission is to empower humanity through advancing collaborative general intelligence. We're building a future where everyone has access to the knowledge and tools to make AI work for their unique needs and goals. We are scientists, engineers, and builders who've created some of the most widely used AI products, including ChatGPT and Character.ai, open-weights models like Mistral, as well as popular open source projects like PyTorch, OpenAI Gym, Fairseq, and Segment Anything. About the Role Thinking Machines builds multimodal-first. We're looking for new team members to advance the science of visual perception and multimodal learning. We think about how vision and language interact at scale. We design architectures that fuse pixels and text, build datasets and evaluation methods that test real-world comprehension, and develop representations that let models ground abstract concepts in the physical world. Our goal is to create multimodal systems that support seamless integration into real-world environments. You'll work at the intersection of visual understanding, multimodal reasoning, and large-scale model training. You'll help develop the architectures, data, and evaluation tools that teach AI to see, understand, and collaborate. The best candidate is curious about multimodal interfaces, has experience running large scale experiments and is comfortable contributing to complex engineering systems. While we are looking for a person with expertise in multimodality, Thinking Machines Lab operates in a unified fashion and expects new hires to work across modalities as one team. This role blends fundamental research and practical engineering, as we do not distinguish between the two roles internally. You will be expected to write high-performance code and read technical reports. It's an excellent fit for someone who enjoys both deep theoretical exploration and hands-on experimentation, and who wants to shape the foundations of how AI learns. Note: This is an "evergreen role" that we keep open on an on-going basis to express interest in this research area. We receive many applications, and there may not always be an immediate role that aligns perfectly with your experience and skills. Still, we encourage you to apply. We continuously review applications and reach out to applicants as new opportunities open. You are welcome to reapply if you get more experience, but please avoid applying more than once every 6 months. You may also find that we put up postings for singular roles for separate, project or team specific needs. In those cases, you're welcome to apply directly in addition to an evergreen role. What You'll Do Own research projects on training and performance analysis of multimodal AI models. Curate and build large-scale datasets and evaluation benchmarks to advance vision capabilities. Work with our data infrastructure engineers, pretraining researchers and engineers, and product team to create frontier multimodal models and the products that leverage them. Publish and present research that moves the entire community forward. Share code, datasets, and insights that accelerate progress across industry and academia. Skills and Qualifications Minimum qualifications: Ability to design, run, and analyze experiments thoughtfully, with demonstrated research judgment and empirical rigor. Understanding of machine learning fundamentals, large-scale training, and distributed compute environments. Proficiency in Python and familiarity with at least one deep learning framework (e.g., PyTorch, TensorFlow, or JAX). Comfortable with debugging distributed training and writing code that scales. Bachelor's degree or equivalent experience in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding. Clarity in communication, an ability to explain complex technical concepts in writing. Preferred qualifications - we encourage you to apply even if you don't meet all preferred qualifications, but at least some: Research or engineering contributions in visual reasoning, spatial understanding, or multimodal architecture design. Experience developing evaluation frameworks for multimodal tasks. Publications or open-source contributions in vision-language modeling, video understanding, or multimodal AI. A strong grasp of probability, statistics, and ML fundamentals. You can look at experimental data and distinguish between real effects, noise, and bugs. PhD in Computer Science, Machine Learning, Physics, Mathematics, or a related discipline with strong theoretical and empirical grounding; or, equivalent industry research experience. Logistics Location: This role is based in San Francisco, California. Compensation: Depending on background, skills and experience, the expected annual salary range for this position is $350,000 - $475,000 USD. Visa sponsorship: We sponsor visas. While we can't guarantee success for every candidate or role, if you're the right fit, we're committed to working through the visa process together. Benefits: Thinking Machines offers generous health, dental, and vision benefits, unlimited PTO, paid parental leave, and relocation support as needed. As set forth in Thinking Machines' Equal Employment Opportunity policy, we do not discriminate on the basis of any protected group status under any applicable law.

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 Imaging-based phenotyping of in vitro biology is at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these image-derived phenotypes and human disease and translating them into actionable outcomes. We are looking for a computational biologist with expertise in microscopy data, including a deep understanding of cell and disease biology and fluency with state-of-the-art analysis techniques. Your expertise will help the team navigate the complexities of developing disease-relevant cell models and analyzing high-throughput phenotypic screens, ensure that the tools being developed are statistically calibrated and effective, that analyses are performed to the highest rigor, and following best practices in the broader scientific community. In this role, you will collaborate closely with experimental biologists and machine learning scientists to help identify novel phenotypes, develop new screening paradigms, and improve our understanding of disease. You will use machine learning, statistical, and bioinformatics methods to process and analyze diverse microscopy modalities as well as other modalities, such as transcriptomics 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 image-derived features extracted from microscopy 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 imaging-based experiments and workflows * Synthesize insights from multimodal analyses (microscopy, spatial proteomics, bulk/single-cell RNA-seq, human cohort data) to uncover disease mechanisms and generate therapeutic hypotheses * Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions * Provide domain expertise in cell biology to guide assay development and biological interpretation of image-derived phenotypes * Communicate findings to cross-functional stakeholders through reports, visualizations, presentations, and publications * Identify novel disease-relevant phenotypes and propose new screening paradigms that translate to actionable program decisions * Contribute to therapeutic target identification by linking phenotypic readouts with genetic and omics signals About You * Ph.D. in computational biology, systems biology, bioengineering, machine learning, or a related discipline, with 3+ years of working experience post graduation * Hands-on experience working with microscopy data, preferably fluorescence and label-free microscopy * An understanding of molecular biology or disease biology (e.g. neurological disorders, metabolic disorders) * Experience with spatial proteomics or transcriptomics * Strong programming skills and proficiency with Python scientific packages (i.e., numpy, pandas) * Ability to communicate effectively and collaborate with people of diverse backgrounds and job functions * Committed to writing well-commented code and documentation, and familiar 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. #LI-Hybrid Please be aware of recruitment scams: we never request payments, all recruitment communications are from @insitro.com, and if in doubt, contact us at ****************. 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 ****************

Who We Are For more than two decades, going our own way has led to countless breakthroughs, bettering the lives of those suffering from rare genetic disease. In 1997 we were founded to make a big difference in small patient populations. Now we seek to make an even greater impact by applying the same science-driven, patient-forward approach that propelled our last 25 years of drug development to larger genetic disorders, as well as genetic subsets of more common conditions. Through our unparalleled expertise in genetics, drug discovery and development, we will continue to develop targeted therapies that address the root cause of the conditions we seek to treat. Applying our knowledge to make a transformative impact is not just a calling, but an obligation to those who will benefit most. The end goal has always been better lives and now we can reach more people in need. Our Culture Our desire to make a positive impact on our patients extends to our employees and BioMarin is committed to fostering an inclusive environment where every person feels seen, valued, and heard - so employees can thrive in all areas of their lives, in and outside of work. We seek to provide an open, flexible, and friendly work environment to empower people and to provide them with the ability to develop their long-term careers. Ultimately, we want to be an organization where people enjoy coming to work and take pride in our efforts to help patients. BioMarin's Research & Development group is responsible for everything from research and discovery to post-market clinical development. Research & Development involves all bench and clinical research and the associated groups that support those endeavors. Our teams work on developing first-in-class or best-in-class therapeutics that provide meaningful advances to patients. Come join our team and make a meaningful impact on patients' lives. Position Overview: We are seeking a motivated Research Associate I with in vivo experience to join the Skeletal and CNP Therapeutic Area group in vivo team to design and execute key studies to transform the lives of people with rare musculoskeletal diseases. The primary role of the Research Associate I will be assisting with the execution of in vivo studies as part of the in vivo team. They will work collaboratively across Research group in the Skeletal and CNP Therapeutic Area group as well as othertherapeutic areas as needed to execute project strategies for in vivo testing of novel therapeutics. The successful candidate will have a background in animal handling, in vivo techniques and demonstrated experience in the use of animal model systems in research. Experience with rodent in vivo models of disease and a collaborative mindset is highly preferred. Experience with skeletal disease biology is desirable. While some industry experience is a plus, it is not required. The successful candidate will contribute to in vivo model evaluation and project teams that support the project goals. Strong written communication skills are critical for IACUC protocols, communicating studyresults, monitoring in vivo studies and tissue collection, and sample management. The successful candidate will have experience with multiple methods of dosing techniques (IM, IP, IV, SC, PO), Necropsy, tissue collection and preferred experience with other in vivo analytic techniques including gait analysis, mechanical evaluation of bone, histology, computerized tomographyand IVIS imaging. The ideal candidate will have a Bachelor's or equivalent scientific degree in Biology or related science. The ideal candidate will have hands-on experience with dosing and data collection in animal models of disease, a proven track record of high-quality science, proficiency with in vivomethods such as administration of test articles, perfusion and tissue collection, blood collection, with rodentsurgical experience preferred. Responsibilities: Support Research Program * Conduct in vivo dosing support and execution of studies including IV, IM, SC, IP, and PO dosing forresearch on genetic skeletal diseases and CNP therapeutic indications * Contribute to novel therapeutic programs based on innovative, ground-breaking discoveries that could lead to new, high-impact opportunities for patients * Participate and collaborate in writing, review and contribution to study synopses, protocols, study reports and regulatory documents * Collaborate with various BioMarin functions to collaboratively ensure timely progression of projects * Excellent written and verbal communication * Ability to build and foster productive cross-functional collaborations both within and external to BioMarin * Execute hands-on responsibilities including but not limited to animal handling and restraint (rodents), administration via various routes of administration, including intravenous (tail-vein), in-life animal health monitoring and measurements, clinical observations, sample collection and processing, and accurate data collection. In addition, providing daily care and monitoring of mice or rats, including health checks and documentation, will also be required. * Follow all institutional, local, and federal regulations regarding animal care and use. Adhere to safety protocols and maintain a clean and organized work environment. Maintain detailed and accurate records of all procedures and animal health status including adverse study events. Meticulous electronic lab notebook documentation. * Communicate experimental plans and results to the project team. Support product development and regulatory filings for pivotal preclinical studies. * Follow instructions and work independently to effectively manage time and prioritize tasks to ensure allassignments are completed on or before deadlines. * Share your knowledge and understanding with other team members * Document experimental methods and outcomes using Electronic Lab Notebooks and generation/maintenance of technical procedure documents and SOPs. * Willingness to work on site full time including off hours and weekends based on study needs. General requirements for the position: * Strong analytical, problem-solving, and decision-making skills * Understanding of genetically engineered models, breeding of rodents * Excellent oral and written communication skills * Passion for contributing your scientific skills to develop therapies for patients in need * Must be able to utilize computer databases for data analysis, data entry, and point of care observations * Must be able to work under time constraints with minimal direction of day-to-day responsibilities, including collaboratively working with multidisciplinary teams * Must be able to work with external regulatory agencies and accreditation groups * Some "off-core business hours" work required * Complete all company training requirements * Perform all work per designated safety standards and comply with Personal Protective Equipment requirements and occupational health to perform work tasks * This position is an on-site critical required position Education and Experience Requirements: * Bachelor's degree in a related subject area or equivalent amount of previous related experience in in vivo study execution * Hands-on experience with animal handling preferred if inclusive of rodent in vivo work. * RA 1 will typically have a minimum of 2 years relevant experience This position is full-time on-site and based in Petaluma, CA with occasional work on site in San Rafael, CA Note: This description is not intended to be all-inclusive, or a limitation of the duties of the position. It is intended to describe the general nature of the job that may include other duties as assumed or assigned. Equal Opportunity Employer/Veterans/Disabled An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. The salary range for this position is: $72,000 to $99,000. BioMarin considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans. For additional benefits information, visit:

Job Description Mercor is seeking computational biology experts to contribute to a unique project with a top-tier AI research organization. This short-term initiative challenges AI models with hidden-answer “mystery problems” grounded in real biological data. Experts will design, validate, and anonymize complex datasets to evaluate model reasoning capabilities, not lookup accuracy. This is a compelling opportunity for data-driven life scientists to shape next-generation AI evaluation benchmarks. 2. Key Responsibilities • Design biologically grounded problems with a single correct answer and ≥20 plausible distractors • Identify, download, and preprocess datasets from public repositories (e.g., GEO, SRA, NCBI) • Subsample and anonymize datasets to prevent metadata-based inference • Independently validate solutions through custom analysis pipelines and visualizations • Operate within technical constraints (e.g., file size, task time limits) 3. Ideal Qualifications • Hands-on experience analyzing sequencing or omics datasets (e.g., RNA-seq, WGS, mass spec) • Proficient with bioinformatics tools and formats (e.g., BLAST, samtools, DESeq2, FASTA/FASTQ/BAM) • Comfortable coding in Python, R, or bash, and working in Jupyter notebooks • Understanding of biological experiment design and lab-to-data nuances (e.g., batch effects) • Advanced degree (MS, PhD) or research background in computational biology, genomics, or bioinformatics 4. More About the Opportunity • Remote and asynchronous - set your own schedule • Expected commitment: 15-20 hours/week • Project duration: ~1 month • Potential for additional projects based on performance and interest 5. Compensation & Contract Terms • $65-85/hour depending on experience and geography • Paid weekly via Stripe Connect • Structured as a freelance contract - independent contractor status 6. Application Process • Submit your resume to get started • Qualified applicants will complete a short form assessing technical experience • Follow-up steps may include a sample task or review call • Responses typically within 3-5 business days 7. About Mercor • Mercor is a talent marketplace that connects top experts with leading AI labs and research organizations. • Our investors include Benchmark, General Catalyst, Adam D'Angelo, Larry Summers, and Jack Dorsey. • Thousands of professionals across domains like law, creatives, engineering, and research have joined Mercor to work on frontier projects shaping the next era of AI.

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.

About the Company We are a seed-stage AI company building the industry standard for evaluating and benchmarking large language models on real enterprise tasks. About the Role As a Research Scientist, you will develop new benchmarks, methodologies, and evaluation pipelines that shape how cutting-edge models are assessed, compared, and deployed in production environments. Your work will directly influence model selection and safety decisions across foundation model labs, high-growth AI product companies, and Fortune-scale enterprises. Responsibilities Benchmarking & Model Analysis Evaluate newly released models as they launch (e.g., Gemini, DeepSeek, etc.) Run large-scale assessment workflows using internal evaluation infrastructure Compare model performance across enterprise-grade task categories Design New Benchmarks from Scratch Identify high-value model application domains through research exploration Construct datasets, including labeling strategy and workforce coordination Write short “white-paper-style” summaries explaining benchmark purpose, method, and findings Advance Automated Evaluation Methodologies Improve systems for scoring generated text beyond standard metrics Explore research in reference-free, rubric-based, and human-aligned evaluation Develop new techniques for reliability, consistency, and repeatability Cross-functional Collaboration Work closely with engineering to scale evaluation infra Partner with customers to refine evaluation relevance and task fit Influence product direction through research insights Qualifications 0-3 years post-grad experience (Master's, PhD, or equivalent applied research) Publications, preprints, or demos showing cutting-edge work Experience with diffusion models, NLP, multimodal, or benchmarking work Ability to operate independently with ambiguity Clean, maintainable research codebases Candidates from: top engineering/research universities applied AI startups well-regarded research internships Required Skills Built or contributed to a benchmark or evaluation methodology Experience in enterprise task model evaluation Stanford / top lab adjacency (per their historical hiring success) Preferred Skills Wants to publish as primary motivation Purely academic with slow timelines Big-tech culture fit concerns (Meta / Google / Salesforce specifically noted-but case-by-case) Pay range and compensation package Base Salary: up to $250K depending on background Equity: typically 0.3% - 0.5%, flexibility for exceptional candidates Rapid equity refresh possible based on impact Equal Opportunity Statement Visa sponsorship available. Relocation support. Health & dental coverage. Lunch + dinner provided, snacks & coffee. Unlimited PTO. Weekly happy hours with community guests. Team events (bowling, hiking, rock climbing, etc.). Swag program (hats, etc.). Work Environment & Culture In-person, San Francisco HQ (required). Core hours: 9-5, some teammates extend voluntarily. Most team members work 1 weekend day per week (flexible). High-ownership, low-ego, collaborative. Live demos Mondays, team lunch Thursdays, community Fridays. Early-stage pace, applied focus-not academic publishing. Tech Environment (while research-focused, exposure beneficial) Backend: Python / Django. Frontend: React + TypeScript. Infra: AWS. Evaluation frameworks + internal tooling. Why This Role Is Unique The company already collaborates with foundation model labs, high-growth AI vertical product companies, and Fortune 500 enterprises (not publicly facing). ChatGPT Vals AI $5M seed raised, runway of 2+ years at current burn. Only one research scientist is being hired-true founding impact. Opportunity to define industry standards for model trust, reliability, and certification. Positioned to become the rating agency for generative AI.

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

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.

We're working with a San Francisco client that's got a research team of 50~ professionals and looking to further expand it. They are specifically looking to flesh out their Research Group by hiring a Research Scientist on a hybrid basis. They have seen $300M in a recent fund raise. Skills targeted: PhD in Physics/ Quantum Physics/ Theory/ Statistics/ Mathematics/ Computational Science or similarly related field. 2+ YoE working with AI Agents. Good exposure to LLMs. Ideally a background in Audio focused research. Alternatively Search, would also be highly advantageous. TC package of $1-1,5M with sizeable base salary & equity package. If that looks of interest, apply & Goliath will be in touch!

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.

Who We Are BioMarin is a global biotechnology company that relentlessly pursues bold science to translate genetic discoveries into new medicines that advance the future of human health. Since our founding in 1997, we have applied our scientific expertise in understanding the underlying causes of genetic conditions to create transformative medicines, using a number of treatment modalities. Using our unparalleled expertise in genetics and molecular biology, we develop medicines for patients with significant unmet medical need. We enlist the best of the best - people with the right technical expertise and a relentless drive to solve real problems - and create an environment that empowers our teams to pursue bold, innovative science. With this distinctive approach to drug discovery, we've produced a diverse pipeline of commercial, clinical and preclinical candidates that have well-understood biology and provide an opportunity to be first-to-market or offer a substantial benefit over existing therapeutic options. About Worldwide Research and Development From research and discovery to post-market clinical development, our WWRD engine involves all bench and clinical research and the associated groups that support those endeavors. Our teams work on developing first-in-class and best-in-class therapeutics that provide meaningful advances to patients who live with genetic diseases. Contract role in This role is onsite five days a week in San Rafael, CA* The Research & Early Development (RED) group is responsible for everything from research and discovery to post-market clinical development. RED involves all bench and clinical research and the associated groups that support those endeavors. Our teams work on developing first-in-class and best-in-class therapeutics that provide meaningful advances to patients who live with rare diseases. Summary Description: Gain industry experience and learn various skills to become a well-rounded scientist capable of advancing drug development. The individual will assist senior staff in planning, performing, and documenting laboratory experiments. Primary responsibilities may include general lab duties, buffer preparation, animal tissue processing, analytical pathology techniques including tissue sectioning (microtomy and cryotomy), histologic staining (e.g. H&E & Masson's trichrome), immunohistochemistry, In Situ Hybridization, and brightfield and epifluorescence microscopy. Other responsibilities include qualitative and basic, quantitative image analysis (Visiopharm), and preparation of image data for power points and reports. The ideal candidate will be responsible for performing, and/or supporting the development and optimization of experimental systems. This role conducts lab-based experimentation based on literature protocols, standard operating procedures (SOPs), consulted innovative approaches, and conducts general laboratory maintenance responsibilities. This role performs data analysis with appropriate documentation of all methods used and proper handling of raw data. Experience & Education per level: Research Associate 1: Bachelor's degree and at least 1-2 years of relevant experience Work Environment/Physical Demands: The employee may frequently be required to sit and talk or hear. The employee is occasionally required to stand; walk; use hands to handle or feel; reach with hands and arms; climb or balance; stoop, kneel, crouch, crawl, and smell. The employee must occasionally lift and/or move up to 25 pounds. Specific vision abilities by this job include close vision, depth perception and ability to adjust focus. Wet lab environment. Some toxic chemical use. Occasional foul odors. Candidate must not have any known chemical allergies. Note: This description is not intended to be all-inclusive, or a limitation of the duties of the position. It is intended to describe the general nature of the job that may include other duties as assumed or assigned. An Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. In the U.S, the salary range for this position is $ 31 to $ 50 per hour. The base pay actually offered will take into account internal equity, and may also vary depending on candidate's geographic region, job-related knowledge, skills, and experience amongst other factors. The salary range for this position is: $31 to $50. BioMarin considers a variety of factors when determining base compensation, including experience, qualifications, and geographic location. These considerations mean actual compensation will vary. This position may also be eligible for a discretionary annual bonus, discretionary stock-based long-term incentives (eligibility may vary based on role), paid time off, and a benefits package. Benefits include company-sponsored medical, dental, vision, and life insurance plans. For additional benefits information, visit:

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.