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Computational Scientist Rdkit Jobs in San Ramon, CA

Chemify Ltd

Staff CADD Scientist

San Francisco, CA · On-site +1

This gives our computational scientists something rare: a direct, high-throughput bridge from in ... RDKit, OpenEye); real experience inside the drug-discovery loop (SAR, MPO, DMTL cycles, lead ...

All JobsComputational Scientist Rdkit JobsComputational Scientist Rdkit Jobs in San Ramon, CA

Computational Scientist Rdkit information

See San Ramon, CA salary details

$56.4K

$124.4K

$153.7K

How much do computational scientist rdkit jobs pay per year?

As of Jul 22, 2026, the average yearly pay for computational scientist rdkit in San Ramon, CA is $124,428.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $153,100.00 per year, depending on experience, location, and employer.

What is a Computational Scientist specializing in RDKit?

A Computational Scientist specializing in RDKit is a professional who uses computational methods and the RDKit cheminformatics toolkit to analyze and model chemical structures and reactions. They often work in fields like drug discovery, materials science, or chemical engineering, leveraging RDKit for tasks such as molecular fingerprinting, property prediction, virtual screening, and data visualization. Their expertise combines advanced programming skills, a strong understanding of chemistry, and the ability to develop or optimize algorithms for chemical data analysis.

What are the key skills and qualifications needed to thrive as a Computational Scientist working with RDKit, and why are they important?

To thrive as a Computational Scientist using RDKit, you need a strong background in cheminformatics, computational chemistry, and programming, typically with an advanced degree in chemistry, bioinformatics, or a related field. Proficiency in Python, familiarity with RDKit libraries, and experience using molecular modeling and data analysis tools are essential. Critical thinking, problem-solving, and effective collaboration are important soft skills for translating scientific questions into computational solutions. These competencies enable accurate molecular data analysis, innovation in research, and successful teamwork in interdisciplinary environments.

What is the difference between Computational Scientist Rdkit vs Computational Chemist?

AspectComputational Scientist RdkitComputational Chemist
Required CredentialsDegree in Chemistry, Bioinformatics, or related; programming skills in Python; familiarity with RDKitDegree in Chemistry, Chemical Engineering, or related; strong background in molecular modeling and programming
Work EnvironmentResearch labs, biotech companies, pharmaceutical firms; focus on software development and data analysisAcademic or industrial labs; focus on experimental design, molecular simulations, and data interpretation
Industry UsageUsed in cheminformatics, drug discovery, and molecular data analysisApplied in pharmaceuticals, materials science, and chemical research

Computational Scientist Rdkit specializes in developing and applying cheminformatics tools using RDKit, often combining programming and data analysis. Computational Chemist focuses on molecular modeling, simulations, and chemical research. While both roles require chemistry knowledge and programming skills, the Computational Scientist Rdkit role emphasizes software development and data processing, whereas the Computational Chemist emphasizes experimental and theoretical chemistry applications.

How does a Computational Scientist working with RDKit typically collaborate with chemists and software engineers on research projects?

Computational Scientists specializing in RDKit often work closely with chemists to translate scientific questions into computational workflows, such as molecule property prediction or virtual screening. They also collaborate with software engineers to integrate RDKit functionalities into larger platforms or to optimize code for performance and scalability. Effective communication and project management are essential, as these interdisciplinary teams rely on regular meetings, shared documentation, and iterative feedback to ensure research goals are met efficiently. This collaborative environment not only fosters scientific innovation but also provides opportunities to learn from experts in related fields.
What are popular job titles related to Computational Scientist Rdkit jobs in San Ramon, CA? For Computational Scientist Rdkit jobs in San Ramon, CA, the most frequently searched job titles are:
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Computational Scientist Rdkit jobs near you

Applied ML Scientist (Staff / Principal)

Genesis Molecular AI

San Mateo, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 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
  • 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.

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