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Rdkit Python Jobs (NOW HIRING)

Chemify Ltd

Staff CADD Scientist

San Francisco, CA · On-site +1

Strong Python and at least one core cheminformatics toolkit (e.g. RDKit, OpenEye); real experience inside the drug-discovery loop (SAR, MPO, DMTL cycles, lead optimisation, library enumeration ...

1910

Computational Theoretical Chemist II

Boston, MA · On-site

Hands-on experience with Python and Bash scripting for automating workflows and data analysis * Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

1910

Computational Theoretical Chemist I

Boston, MA · On-site

Hands-on experience with Python and Bash scripting for automating workflows and data analysis * Familiarity with cheminformatics toolkits such as RDKit for molecular property prediction and data ...

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All JobsRdkit Python Jobs

Rdkit Python information

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How much do rdkit python jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for rdkit python in the United States is $58.62, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $66.59 per hour, depending on experience, location, and employer.

What is the difference between Rdkit Python vs Chemoinformatics Software Developer?

AspectRdkit PythonChemoinformatics Software Developer
Required CredentialsPython programming, cheminformatics knowledge, basic chemistry backgroundComputer science or chemistry degree, programming skills, cheminformatics understanding
Work EnvironmentResearch labs, biotech, pharmaceutical companies, open-source projectsSoftware development teams, biotech firms, research institutions
Industry UsageData analysis, molecule modeling, property predictionDeveloping cheminformatics tools, software solutions, data management

Rdkit Python is primarily a cheminformatics library used for molecule analysis and modeling, while a Chemoinformatics Software Developer designs and builds software tools for chemical data management. Both roles require programming skills and chemistry knowledge but differ in focus: one is a specialized library, the other a software development position within the industry.

What is an RDKit Python developer?

An RDKit Python developer is a programmer who specializes in using the RDKit library with the Python programming language to perform cheminformatics tasks. RDKit is an open-source toolkit that enables the analysis and manipulation of chemical structures, including tasks such as molecule visualization, substructure searching, and property calculation. Developers in this role often work in pharmaceutical, biotech, or research organizations to build software solutions for drug discovery, chemical informatics, or molecular modeling. They typically have experience with Python programming, chemistry concepts, and data analysis.

What are the key skills and qualifications needed to thrive as an RDKit Python Developer, and why are they important?

To thrive as an RDKit Python Developer, a strong background in chemistry or cheminformatics, proficiency in Python programming, and familiarity with molecular modeling concepts are essential. Experience with RDKit, chemical informatics libraries, and related tools like Jupyter Notebooks or data analysis frameworks is typically required. Strong problem-solving, attention to detail, and effective communication skills help in collaborating with scientific teams and interpreting complex data. These skills are crucial for developing robust cheminformatics solutions, ensuring accurate data analysis, and advancing research or drug discovery projects.

What are the typical daily tasks for a professional using RDKit with Python in a cheminformatics role?

Professionals working with RDKit and Python in cheminformatics typically spend their days developing and optimizing workflows for molecular data analysis, such as calculating molecular descriptors, generating fingerprints, and performing substructure searches. They often collaborate with chemists and data scientists to preprocess chemical datasets, visualize molecular structures, and integrate RDKit functionality into larger pipelines for drug discovery or materials science projects. Additionally, maintaining and updating scripts, ensuring data quality, and troubleshooting code are important aspects of the role. Regular communication with cross-functional teams helps align computational efforts with research or business objectives.
Infographic showing various Rdkit Python job openings in the United States as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% Remote job distribution, with an average salary of $121,932 per year, or $58.6 per hour.

Applied ML Scientist (Staff / Principal)

Genesis Molecular AI

San Mateo, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 8 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.

Apply