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Machine Learning Chemistry Jobs (NOW HIRING)

Elicit

Machine Learning Engineer

Oakland, CA

Machine Learning Engineer Elicit is building the reasoning layer for science and decision-making ... Build a target-assessment workflow that combines literature, genetics, chemistry, clinical ...

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How much do machine learning chemistry jobs pay per hour?

As of Jun 18, 2026, the average hourly pay for machine learning chemistry in the United States is $22.26, according to ZipRecruiter salary data. Most workers in this role earn between $18.27 and $24.52 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Chemistry position, and why are they important?

To thrive in a Machine Learning Chemistry role, you need a solid background in chemistry, expertise in data science and machine learning algorithms, and typically an advanced degree in chemistry, computer science, or a related field. Familiarity with programming languages like Python or R and experience working with cheminformatics tools and machine learning frameworks (such as TensorFlow or scikit-learn) are essential. Strong analytical thinking, problem-solving abilities, and effective communication skills enable professionals to bridge the gap between computational work and experimental research teams. These competencies are crucial for developing innovative solutions in chemical research and ensuring successful collaboration across interdisciplinary teams.

What is a Machine Learning Chemistry job?

A Machine Learning Chemistry job involves using artificial intelligence techniques to analyze chemical data, model molecular behaviors, and accelerate discoveries in chemistry-related fields. Professionals in this role develop and apply machine learning algorithms to predict chemical properties, optimize reactions, and assist in drug design, material science, and other applications. They typically work in pharmaceuticals, materials science, or environmental chemistry, collaborating with chemists, data scientists, and engineers to solve complex chemical problems efficiently.

What are the typical projects and daily responsibilities for someone working in Machine Learning Chemistry?

Professionals in Machine Learning Chemistry often work on projects such as developing predictive models for chemical property analysis, optimizing molecular structures, or advancing drug discovery through data-driven methods. Daily tasks may include data preprocessing, building and training machine learning models, validating results, and interpreting outcomes in collaboration with experimental chemists. Teamwork is common, with regular interactions between chemistry researchers, data scientists, and software engineers. This structure allows for iterative feedback and ensures that computational models align with practical lab needs. Continuous learning and adaptation are also key, as both the chemistry and machine learning fields are rapidly evolving.

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What cities are hiring for Machine Learning Chemistry jobs? Cities with the most Machine Learning Chemistry job openings:
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Machine Learning Chemistry jobs near you
Infographic showing various Machine Learning Chemistry job openings in the United States as of June 2026, with employment types broken down into 8% Internship, 53% Full Time, 31% Part Time, and 8% Temporary. Highlights an 100% In-person job distribution, with an average salary of $46,292 per year, or $22.3 per hour.

Senior / Staff Machine Learning Scientist

Chemify Ltd

San Francisco, CA • On-site

Full-time

Posted 5 days ago

Job description

About Chemify:
Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world's largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity.
Our Chemifarm facility in Glasgow operates a growing fleet of advanced robotic systems that automate synthesis, optimisation, and library generation. This gives our computational scientists something rare: a direct, high-throughput bridge from in silico design to physically synthesised molecules, closing the design-make-test loop at a pace conventional drug discovery organisations cannot match.
Location: San Francisco (hybrid)
Travel: Regular travel to our Glasgow HQ / Chemifarm
The Role
We are seeking a Senior / Staff Machine Learning Scientist to work across the breadth of Chemify's platform - generative models for chemistry, search and planning for retrosynthesis, computer vision for telemetry from our robotic systems, and agentic workflows that tie it all together. You will partner with computational chemists, CADD scientists, software engineers, and hardware engineers, and apply AI/ML to build the next generation of Chemify's platform.
What sets this role apart is the combination of breadth of ML problems - generative chemistry, vision, search, agents - paired with a robotic platform that turns your models into physical experiments.
If working across a wide range of hard ML problems on a real-world platform sounds like the right shape of job for you, we'd love to welcome you to our team.
Key Responsibilities
  • Build generative and foundation chemistry models for molecular design.
  • Advance retrosynthesis and synthesis-aware ML by leveraging Chemify's reaction database and robot-execution data.
  • Apply computer vision to transform robot telemetry into models that monitor process state and feedback into experimental control.
  • Prototype agentic workflows that orchestrate models, tools, and the platform - closing loops between proposal, execution, observation, and learning.
  • Productionise models into a reproducible, API-first toolkit; partner with Infrastructure on GPU training and HPC; maintain high standards of ML best practices, including rigorous evaluation, benchmarks, and reproducibility.
  • Mentor junior ML scientists, partner with the Head of Advanced Machine Learning on hiring and growth, and represent Chemify's AI/ML capability externally.
  • (Staff level) Set technical direction across the AI/ML stack; lead cross-cutting initiatives spanning chemistry models, retrosynthesis, vision, and agents.

About You
You are an experienced ML scientist who is equally comfortable training models and shipping the code that other people end up building on. You care about whether your model changes a real decision - not just whether it beats a benchmark. You're at home moving across problem types, from generative models to vision to search.
We expect you to bring:
  • PhD or equivalent experience in Machine Learning, Computer Science, Statistics, Physics, or a related quantitative field - 5+ years (Senior) or 8+ years (Staff) of hands-on applied ML experience, including production-grade work.
  • Deep familiarity with modern deep learning stack (PyTorch or JAX), and breadth across at least two of: generative models (diffusion, autoregressive, flow-based), graph and equivariant networks, vision (CNNs, ViTs, multimodal LLMs), search and planning (MCTS, A*), or agentic / RL systems.
  • Experience taking ML from prototype to production: reproducible pipelines, distributed jobs, and batch workflows on cloud (AWS / GCP / Azure) or HPC.
  • Strong scientific computing instincts: clean Python, careful experiment design, leakage-aware splits, and rigorous benchmarks.
  • Clear communication with non-ML scientists and engineers and a willingness to pick up new domains (you don't need to know chemistry on day one).
  • (Staff level) A track record of technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects.

Beneficial Skills
  • Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real-world loops.
  • Familiarity with retrosynthesis ML, computer-aided synthesis planning (CASP), or reaction-condition / yield prediction.
  • Working knowledge of how ML fits into a drug-discovery or materials-design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) - or willingness to pick these up.
  • MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models.
  • A visible track record in the field - peer-reviewed publications, open-source contributions, or public projects that demonstrate your judgement on real ML problems.

Why Join Chemify?
Impact:
Your models will directly shape what Chemify's robotic platform proposes, plans, and observes - at a company uniquely positioned to close the loop between design and physical experiment.
Autonomy:
Reporting to the Head of Advanced Machine Learning, you will work across the AI/ML problems with the most impact, and have meaningful influence over the direction of our AI/ML capability.
Ambition:
We are a Series B deep-tech company investing in world-class infrastructure and tackling problems at the frontier of AI, robotics, and chemistry. You will have the resources and the mandate to do AI/ML in a way that isn't possible elsewhere - across chemistry, vision, search, and autonomous systems on the same platform.

Apply