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Machine Learning Computational Chemistry Jobs in California

Iambic Therapeutics, Inc

$124K - $172K/yr

You will work in a cross-functional team, collaborating closely with machine learning scientists ... This is a hands-on role, requiring technical expertise in computational chemistry, experience with ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

You will leverage in-house computational tools and contribute to the design, training, and evaluation of new machine learning-based methods. Depending on your assignment, this position may offer a ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

$9.7K/wk

You will leverage in-house computational tools and contribute to the design, training, and evaluation of new machine learning-based methods. Depending on your assignment, this position may offer a ...

LLNL

Machine Learning (ML) Bioengineer

Livermore, CA · On-site

You will leverage in-house computational tools and contribute to the design, training, and evaluation of new machine learning-based methods. Depending on your assignment, this position may offer a ...

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All JobsMachine Learning Computational Chemistry JobsMachine Learning Computational Chemistry Jobs in California

Machine Learning Computational Chemistry information

See California salary details

$24K

$112.1K

$207.1K

How much do machine learning computational chemistry jobs pay per year?

As of Aug 22, 2026, the average yearly pay for machine learning computational chemistry in California is $112,091.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,400.00 and $151,290.00 per year, depending on experience, location, and employer.

What is machine learning computational chemistry?

Machine learning computational chemistry is a field that combines machine learning techniques with computational chemistry to accelerate the discovery and design of molecules and materials. By training algorithms on large datasets of chemical information, researchers can predict molecular properties, simulate chemical reactions, and optimize compounds more efficiently than traditional methods. This approach helps reduce the time and cost required for research in drug discovery, materials science, and related fields.

What are some common challenges faced by professionals working in machine learning computational chemistry roles?

One common challenge in Machine Learning Computational Chemistry roles is integrating large and often complex chemical datasets with appropriate machine learning models, which requires a solid understanding of both domains. Professionals may also encounter difficulties in ensuring that their models are both interpretable and generalizable to new data, as overfitting is a frequent issue. Additionally, collaboration with chemists and data scientists is essential, so clear communication across disciplines is key to success. Staying up to date with the latest developments in both computational chemistry and machine learning is crucial for ongoing professional growth.

What are the key skills and qualifications needed to thrive as a machine learning computational chemist, and why are they important?

To thrive as a Machine Learning Computational Chemist, you need a solid background in chemistry, mathematics, and computer science, typically supported by an advanced degree in computational chemistry, cheminformatics, or a related field. Proficiency with programming languages (such as Python), machine learning frameworks (like TensorFlow or PyTorch), and molecular modeling software is essential. Strong analytical thinking, problem-solving skills, and effective collaboration are key soft skills that help drive innovation and teamwork. These skills and qualifications are critical for developing accurate models, advancing research, and translating computational insights into real-world chemical solutions.

What is the difference between Machine Learning Computational Chemistry vs Computational Chemist?

AspectMachine Learning Computational ChemistryComputational Chemist
Required CredentialsAdvanced degrees in chemistry, computer science, or related fields; knowledge of machine learning and programmingDegree in chemistry, chemical engineering, or related fields; strong background in chemical theory and modeling
Work EnvironmentResearch labs, tech companies, academia; focus on algorithm development and data analysisLaboratories, research institutions, industry; focus on chemical modeling and simulation
Employer & Industry UsageTech firms, pharmaceutical companies, research institutions applying AI/ML techniquesPharmaceutical, chemical, and materials industries conducting chemical research and development

Machine Learning Computational Chemists specialize in applying machine learning algorithms to chemical data, enhancing predictive models and simulations. Computational Chemists focus on traditional chemical modeling and simulations using computational methods. Both roles require strong chemistry backgrounds, but Machine Learning Computational Chemists emphasize data science and AI skills, while Computational Chemists focus on chemical theory and modeling techniques.

What are popular job titles related to Machine Learning Computational Chemistry jobs in California?

For Machine Learning Computational Chemistry jobs in California, the most frequently searched job titles are:

What job categories do people searching Machine Learning Computational Chemistry jobs in California look for?

The top searched job categories for Machine Learning Computational Chemistry jobs in California are:

What cities in California are hiring for Machine Learning Computational Chemistry jobs?

Cities in California with the most Machine Learning Computational Chemistry job openings:

Machine Learning Computational Chemistry jobs near you

Computational Chemistry/Physics (MS/BS)

MixMode

San Francisco, CA • On-site

$85 - $110/hr

Other

Posted 4 days ago

Job description

Job Description

We’re looking for a computational chemistry or physics researcher to help build and deploy physics-based simulation methods for molecular and materials systems. This role emphasizes strong fundamentals, excellent coding, and the ability to turn theory into reliable software.

What You’ll Do
  • Implement and extend physics-based models and algorithms for molecular and materials simulations
  • Translate theoretical ideas into efficient, well-tested numerical methods
  • Write high-performance Python and/or C++ code, with exposure to parallel or accelerator computing
  • Contribute to simulation pipelines, validation, and scaling of new methods
  • Work closely with senior scientists in a highly collaborative, fast-moving research environment
Who You Are
  • MS or BS in chemistry, physics, applied physics, materials science, or a related field
  • Solid foundation in quantum mechanics, statistical mechanics, and thermodynamics
  • Strong scientific programming skills in Python and/or C++
  • Comfortable working with mathematical models and numerical methods
  • Self-directed, curious, and eager to learn new theory and tools
Nice to Have
  • Experience with molecular simulation or electronic structure codes
  • Exposure to parallel programming (OpenMP, MPI, CUDA, or similar)
  • Prior research experience in computational chemistry, physics, or materials science
Why Azulene Labs
  • Opportunity to work on foundational scientific problems with real-world impact
  • Significant responsibility and ownership early in your career
  • Culture focused on rigor, learning, and building things that last
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