Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization. * Experience with large-scale data management, including ...
Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization. * Experience with large-scale data management, including ...
... Bayesian optimization * Guide the use of multimodal biological datasets including sequence, structure, and experimental assay data. Platform Integration & Model Deployment * Lead development of ...
... Bayesian optimization * Guide the use of multimodal biological datasets including sequence, structure, and experimental assay data. Platform Integration & Model Deployment * Lead development of ...
... Bayesian optimization * Guide the use of multimodal biological datasets including sequence, structure, and experimental assay data. Platform Integration & Model Deployment * Lead development of ...
... Bayesian optimization * Guide the use of multimodal biological datasets including sequence, structure, and experimental assay data. Platform Integration & Model Deployment * Lead development of ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site +1
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site +1
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
... Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning ... the creation and optimization of efficient models (e.g., model compression, quantization ...
... Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning ... the creation and optimization of efficient models (e.g., model compression, quantization ...
Staff CADD Scientist
San Francisco, CA · On-site +1
Familiarity with active learning, iterative DMTL design loops, and Bayesian optimisation applied to molecular design. * Experience building or integrating CADD tooling into API-first platforms ...
Staff CADD Scientist
San Francisco, CA · On-site +1
Familiarity with active learning, iterative DMTL design loops, and Bayesian optimisation applied to molecular design. * Experience building or integrating CADD tooling into API-first platforms ...
Design and iterate models that estimate fair market value, recovery potential, and optimal ... Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling)
Design and iterate models that estimate fair market value, recovery potential, and optimal ... Strong modeling and experimentation skills (Python, SQL, Bayesian / probabilistic modeling)
Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real-world loops. * Familiarity with retrosynthesis ML, computer ...
Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real-world loops. * Familiarity with retrosynthesis ML, computer ...
Research Scientist - Frontier AI/ML & Quantum Algorithms
San Francisco, CA · On-site
$200K - $300K/yr
Optimization, sampling, amortized inference, sequential decision-making, Bayesian experimental design, reinforcement learning, planning, and control. * Scientific reasoning systems, model-guided ...
Research Scientist - Frontier AI/ML & Quantum Algorithms
San Francisco, CA · On-site
$200K - $300K/yr
Optimization, sampling, amortized inference, sequential decision-making, Bayesian experimental design, reinforcement learning, planning, and control. * Scientific reasoning systems, model-guided ...
... 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 ...
... 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 ...
Quantitative Geneticist
San Francisco, CA · On-site +1
... 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 ...
Quick apply
Quantitative Geneticist
San Francisco, CA · On-site +1
... 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 ...
Quantitative Geneticist
South San Francisco, CA · On-site +1
... 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 ...
Quantitative Geneticist
South San Francisco, CA · On-site +1
... 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 ...
Senior Data Scientist
San Ramon, CA · On-site
$100 - $105/hr
Model Development, Evaluation & Optimization * Data Visualization & Executive Presentations * Cloud ... Experience with forecasting, Bayesian networks, and graph analytics * Utility/Energy industry ...
Senior Data Scientist
San Ramon, CA · On-site
$100 - $105/hr
Model Development, Evaluation & Optimization * Data Visualization & Executive Presentations * Cloud ... Experience with forecasting, Bayesian networks, and graph analytics * Utility/Energy industry ...
Senior Research Engineer
Santa Clara, CA · On-site
$200K/yr
Formulate and solve complex inference problems using Bayesian estimation, filtering, optimization, and related statistical techniques * Prototype, evaluate, and refine algorithms using large-scale ...
New
Quick apply
Senior Research Engineer
Santa Clara, CA · On-site
$200K/yr
Formulate and solve complex inference problems using Bayesian estimation, filtering, optimization, and related statistical techniques * Prototype, evaluate, and refine algorithms using large-scale ...
New
Senior Data Scientist
San Francisco, CA · On-site
... modeling • Bayesian hypothesis testing • Understanding how teams run experiments • B2B ... optimization, math, statistics, etc. • Have built and extensively used data pipelines in a ...
Senior Data Scientist
San Francisco, CA · On-site
... modeling • Bayesian hypothesis testing • Understanding how teams run experiments • B2B ... optimization, math, statistics, etc. • Have built and extensively used data pipelines in a ...
Sr. Analyst, Product Analytics
San Mateo, CA · Hybrid
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
Sr. Analyst, Product Analytics
San Mateo, CA · Hybrid
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
... or optimizing machine learning models, systems, platforms, or methods. Preferred Qualifications ... Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning ...
... or optimizing machine learning models, systems, platforms, or methods. Preferred Qualifications ... Bayesian deep learning, equivariant CNNs, Bayesian optimizations, reinforcement learning ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
Sr. Analyst, Product Analytics
San Mateo, CA · On-site
$175K - $248K/yr
... frameworks, and Bayesian experimentation; designing multi-dimensional test structures and ... optimization decisions; and utilizing Python, R, SQL, Adobe Analytics, Customer Journey Analytics ...
Senior Machine Learning Engineer
San Jose, CA · On-site
$143K - $189K/yr
We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... Bayesian Analysis and others to develop and evaluate algorithms for improving product/system ...
Senior Machine Learning Engineer
San Jose, CA · On-site
$143K - $189K/yr
We use Machine Learning, Reinforcement Learning, AI, Control and Optimization Systems, and Auction ... Bayesian Analysis and others to develop and evaluate algorithms for improving product/system ...
Data Scientist
Culver City, CA · On-site
Strong foundation in statistics, regression, time-series analysis, causal inference, and optimization, with familiarity in Bayesian MMM, hierarchical models, or probabilistic forecasting. 3+ years of ...
Data Scientist
Culver City, CA · On-site
Strong foundation in statistics, regression, time-series analysis, causal inference, and optimization, with familiarity in Bayesian MMM, hierarchical models, or probabilistic forecasting. 3+ years of ...
Bayesian Optimization information
What is the difference between Bayesian Optimization vs Data Scientist?
| Aspect | Bayesian Optimization | Data Scientist |
|---|---|---|
| Primary Focus | Optimizing complex functions and hyperparameters | Analyzing data, building models, deriving insights |
| Required Skills | Statistics, probability, machine learning, programming | Statistics, programming, data analysis, visualization |
| Work Environment | Research labs, AI/ML teams, R&D departments | Business, tech companies, consulting firms |
| Common Tools | Python, R, Bayesian libraries (e.g., GPy, scikit-optimize) | Python, R, SQL, visualization tools |
Bayesian Optimization is a specialized technique used within machine learning and AI to efficiently tune hyperparameters or optimize functions. Data Scientists often utilize Bayesian Optimization as part of their toolkit but have broader responsibilities, including data analysis, modeling, and reporting. While Bayesian Optimization focuses on optimization tasks, Data Scientists work on understanding and interpreting data to inform business decisions.
What are popular job titles related to Bayesian Optimization jobs in California? For Bayesian Optimization jobs in California, the most frequently searched job titles are:
What job categories do people searching Bayesian Optimization jobs in California look for? The top searched job categories for Bayesian Optimization jobs in California are:
What cities in California are hiring for Bayesian Optimization jobs? Cities in California with the most Bayesian Optimization job openings:
Full-time
Medical, Dental, Vision, Life, Retirement, PTO
Posted 21 days ago
Job description
About the Team
Join a world-class team at the forefront of AI and biochemistry.
At Genesis Molecular AI, we're a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don't just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.
About the Role
This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines.
You will act as both a translator and a strategist, ensuring our research is aimed at the most critical challenges and that our drug hunters can leverage the full power of our industry-leading AI platform. This role requires a deep understanding of cheminformatics, computational chemistry, and experimental techniques, strong data science skills, and a talent for communicating complex ideas to a diverse, multidisciplinary team.
Positions are available at various levels of seniority: Senior, Staff, and Principal.
What You'll Do
You are
Nice to have's
Compensation, Benefits, and Perks
About Genesis Molecular AI
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars.
Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.
Join a world-class team at the forefront of AI and biochemistry.
At Genesis Molecular AI, we're a tight-knit team of proven deep learning researchers, software engineers, and drug discovery pioneers. Our shared mission is nothing short of revolutionary: to forge the next generation of AI foundation models that will unlock groundbreaking therapies for patients with severe diseases.
We don't just apply machine learning to biology; we are conducting fundamental research at the intersection of machine learning, physics, and computational chemistry, pushing the boundaries of each field. You will work side-by-side with top multidisciplinary researchers to design and build generative foundation models at scale, having access to ample compute and large-scale simulations.
About the Role
This unique role is for a scientist who is passionate about being a catalyst for applying cutting-edge AI to solve real-world drug discovery challenges. You will be the critical bridge between our long-term research and our experimental drug discovery programs. Your mission is to build, evaluate, monitor, and improve our state-of-the-art models directly into active drug programs, leading the charge on model validation, deployment, and analysis to guide the discovery of new medicines.
You will act as both a translator and a strategist, ensuring our research is aimed at the most critical challenges and that our drug hunters can leverage the full power of our industry-leading AI platform. This role requires a deep understanding of cheminformatics, computational chemistry, and experimental techniques, strong data science skills, and a talent for communicating complex ideas to a diverse, multidisciplinary team.
Positions are available at various levels of seniority: Senior, Staff, and Principal.
What You'll Do
- Work directly with project teams to assess model performance and utility, including applicability to current project needs, and collaborate with ML and engineering teams to resolve issues or add new functionality.
- Assist experimental colleagues with use and interpretation of model predictions by providing context about model quality and prediction uncertainty.
- Evaluate model quality by validating predictions against project data and internal or external benchmarks.
- Curate internal and external datasets for model training and validation (in collaboration with experimental teams).
- Contribute to design and analysis of experiments on model changes and alternative architectures.
You are
- A seasoned computational scientist with a proven track record of machine learning based methods to impact small molecule drug discovery projects.
- A cheminformatics expert, fluent in the language of molecular data with hands-on mastery of tools like RDKit or OpenEye.
- A scientist who speaks the language of experimental drug discovery, with a strong familiarity with common assay types (biochemical/binding/cell-based assays, in vivo studies, etc.) and CADD workflows (docking, virtual screening, ADME prediction, etc.).
- A rigorous data scientist, with experience inmodeling and analysis of small molecule datasets and passion for statistical validation, uncertainty quantification, and deriving clear insights from complex, noisy data.
- A hands-on applied scientist and software engineer with strong coding skills in Python and a deep practical knowledge of the applied ML toolkit (e.g., scikit-learn, PyTorch).
- An exceptional communicator and collaborator, able to act as the bridge between machine learning researchers and experimental scientists.
- A curious, problem-oriented mind, excited to dive into the emerging field at the intersection of AI, physics, chemistry, and biology and make foundational contributions and discoveries.
- A true team player who thrives in highly collaborative, mission-driven environments where science and engineering are deeply intertwined.
- Inspired by our culture of intellectual curiosity and the shared belief that breakthroughs happen when diverse perspectives and minds unite.
Nice to have's
- A PhD in Cheminformatics, Computational Chemistry, Computer Science, or a related field.A track record of publications applying machine learning to drug discovery challenges.
- Deep expertise in advanced modeling techniques such as graph neural networks, multitask modeling, active learning, or Bayesian optimization.
- Experience with large-scale data management, including SQL databases and data pipelining tools.
- Strong opinions on molecule featurization and model validation.
Compensation, Benefits, and Perks
- Competitive compensation package that includes salary and equity.
- Comprehensive health benefits: Medical, Dental, and Vision (covered 100% for the employees).
- 401(k) plan.
- Open (unlimited) PTO policy.
- Free lunches and dinners at our offices.
- Paid family leave (maternity and paternity).
- Life and long- and short-term disability insurance.
About Genesis Molecular AI
Genesis Molecular AI is pioneering foundation models for molecular AI to unlock a new era of drug design and development. Our generative and predictive AI platform, GEMS (Genesis Exploration of Molecular Space), integrates AI and physics into industry-leading models to generate and optimize drug molecules, including the breakthrough generative diffusion model Pearl for structure prediction. Genesis is backed by premier AI and life science investors, including a16z, NVIDIA, Rock Springs Capital, Menlo Ventures, T. Rowe Price, Fidelity, and Radical Ventures. Genesis has also signed category-leading AI-pharma deals, the most recent of which was a significant expansion with Incyte (see coverage in Forbes and GEN) with a total potential deal value of several billion dollars.
Genesis is headquartered in San Mateo, CA, with a fully integrated laboratory in San Diego. We are proud to be an inclusive workplace and an Equal Opportunity Employer.