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Machine Learning Computational Chemistry Jobs in California

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Machine Learning Computational Chemistry information

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$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

Senior Scientist, Computational Chemistry

Neurocrine Biosciences

San Diego, CA

$97K - $132K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 9 days ago

Job description

Who We Are:

Neurocrine Biosciencesis a leading biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering, developing and commercializing life-changing treatments for patients with under-addressed neurological, psychiatric, endocrine and immunological disorders. The company's diverse portfolio includes FDA-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, hyperphagia in Prader-Willi syndrome, endometriosis* and uterine fibroids*, as well as a robust pipeline including multiple compounds in mid- to late-phase clinical development across our core therapeutic areas. For more than three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders, because you deserve brave science. For more information, visitneurocrine.com, and follow the company onLinkedIn,X, Facebook and YouTube. (*in collaboration with AbbVie)


About the Role:Responsible for driving the execution of computational driven methodologies to help design optimized compounds with balanced properties (targets, DMPK, in-vivo) in drug discovery programs. Provides impactful insights and collaboration on projects ranging from early lead identification to the late-stage optimization of advanced projects. Serves as a subject matter expert in 1 or more molecular discovery approaches such as: Structure-based Design & FEP, Virtual Screening, Quantum Chemistry, Machine Learning / Modern AI etc. Responsible for the communication and presentation of computationally derived results to the discovery project teams to facilitate effective decision-making & demonstrate an independent work style while being fully collaborative & team-oriented.

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Your Contributions (include, but are not limited to):

  • This is an on-site role requirement (in San Diego site)

  • Prior experience with independently driving drug discovery projects is highly desired for this role

  • Domain knowledge of most or all the following: Physical Chemistry, Computational Chemistry, Cheminformatics, Protein Modeling/ Molecular Dynamics, Molecular Modeling as employed for the optimization of lead compounds

  • Molecular Modeling applied to compound design and optimization such as Pharmacophore Analyses, Library Design, virtual HTS, Diversity/Similarity Analyses, Scaffold Hopping

  • Protein-Ligand Modeling that includes well-known commercial docking tools as well as Molecular Dynamics methods, & experience with post-docking processing

  • Develops advanced Machine Learning/AI in-silico models for modeling DMPK/in-vitro Biology endpoints, for front-loading projects with appropriate predictive information, & enable more efficient MPO analyses & new compound designs

  • May have an exposure to harnessing large datasets including public domain datasets of chemistry related to various targets and/or chemogenomic nature

  • Ability to demonstrate an overall application of several integrated approaches (ex: ML derived predictions, Modeling SBD/ LBD) to progress compound design contextual in drug discovery, exhibiting innovative approaches that tweak commercial solutions

  • Independently driving forward Drug Discovery projects involving Structure Based Design including, but not limited to, target protein flexibility considerations

  • Serves as an independent Comp Chem representative on Project teams, and works with minimal additional guidance, while demonstrating clear impact on project's chemical series evolution

  • Advances the company's computational platform with expert knowledge providing innovative ideas to make significant contributions, that is aligned with team's strategy to progress compounds forward for multiple projects

  • Leads 1-2 advanced technology platforms, defining new computational methods, in tandem with self-interest and relevance to projects, to help augment Neurocrine's Computational Chemistry platform for Drug Discovery

  • Engages stakeholders from multiple Research functions to deliver and/or exchange key results

  • Drives and/or aligns with strategies emanating from project teams, department and computational chemistry group

  • Provides training and/or supervision to junior staff, as needed

  • Other duties as assigned

Requirements:

  • BS/BA degree in Chemistry and 5+ years of relevant experience, including familiarity utilizing any or all of the following: Protein-Ligand modeling, Molecular Dynamics, Homology Modeling is preferred OR

  • MS/MA degree in Chemistry and 3+ years of similar experience noted above OR

  • PhD in Computational Chemistry or related field and some relevant experience. Postdoctoral experience in Cheminformatics preferred

  • Experience in one or more of the following Molecular Modeling domains is highly desirable: Protein Ligand docking & post-docking processing, Molecular Dynamics, Homology Modeling, Quantum Chemistry, Pharmacophore Analyses and Diversity Analyses

  • Comfortable with routine programming & scripting including python, C++ and/or R

  • Working knowledge about computational technologies for the assessment of early-stage targets (ex: druggability)

  • Familiarity with well-known commercial molecular modeling software suites is also desirable such as Schrodinger, CCG or Open Eye

  • Demonstrates solid level of understanding project / group goals and methods

  • Consistently recognizes anomalous and inconsistent results and interprets experimental outcomes

  • Able to explain the process behind the data and implications of the results

  • Strong knowledge of one or more scientific disciplines, becoming expert in one discipline

  • Strong knowledge of scientific principles, methods and techniques

  • Strong knowledge and demonstrated ability working with a variety of laboratory equipment/tools

  • Ability to work as part of a team; may train lower levels

  • Excellent computer skills

  • Strong communications, problem-solving, analytical thinking skills

  • Detail oriented yet can see broader picture of scientific impact on team

  • Ability to meet multiple deadlines, with a high degree of accuracy and efficiency

  • Strong project management skills

  • A collaborative & team-oriented mindset is essential

#LI-LS1

Neurocrine Biosciences is an EEO/Disability/Vets employer.

We are committed to building a workplace of belonging, respect, and empowerment, and we recognize there are a variety of ways to meet our requirements. We are looking for the best candidate for the job and encourage you to apply even if your experience or qualifications don't line up to exactly what we have outlined in the job description.

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The annual base salary we reasonably expect to pay is $110,800.00-$151,000.00. Individual pay decisions depend on various factors, such as primary work location, complexity and responsibility of role, job duties/requirements, and relevant experience and skills. In addition, this position offers an annual bonus with a target of 20% of the earned base salary and eligibility to participate in our equity based long term incentive program. Benefits offered include a retirement savings plan (with company match), paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage in accordance with the terms and conditions of the applicable plans.

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