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Machine Learning Chemistry Jobs in Massachusetts

JobRx, Inc.

Computational Chemistry Lead

Cambridge, MA · On-site

$119 - $170/hr

Computational Chemistry About Astellas Astellas is a global life sciences company committed to ... Use cheminformatics and machine learning tools to analyze SAR, ADME/Tox profiles, and predict ...

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1910

Computational Theoretical Chemist II

Boston, MA · On-site

Teach key computational chemistry principles to your cross-disciplinary colleagues from Medicinal Chemistry, AI Research, Machine Learning Engineering, Cell Biology, and Pharmacology * Partner to ...

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Machine Learning Chemistry information

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How much do machine learning chemistry jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for machine learning chemistry in Massachusetts is $24.31, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $26.78 per hour, depending on experience, location, and employer.

What is a machine learning chemistry?

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 does a machine learning chemistry do?

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.

What are the key skills and qualifications needed to thrive in machine learning chemistry?

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 are popular job titles related to Machine Learning Chemistry jobs in Massachusetts?

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

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

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

Machine Learning Chemistry jobs near you
Infographic showing various Machine Learning Chemistry job openings in Massachusetts as of August 2026, with employment types broken down into 4% Internship, 76% Full Time, 16% Part Time, and 4% Nights. Highlights an 100% In-person job distribution, with an average salary of $50,556 per year, or $24.3 per hour.

Principal Scientist/Sr. Principal Scientist, Computational Chemistry & Molecular Design

Antares Therapeutics

Boston, MA • On-site

$185K - $240K/yr

Full-time

Re-posted 23 hours ago

Job description

Salary Band: $185,000-$240,000
Location: Downtown Boston, MA (In-Office 2-3 days/week)
Position Overview
We are seeking an exceptional computational chemist to serve as a scientific leader in molecular design across our discovery portfolio. As a member of a highly integrated team of medicinal chemists, machine learning scientists, structural biologists, biologists, and chemical biologists, you will apply and advance the full range of modern computational methods - structure- and ligand-based design, molecular dynamics, free energy perturbation (FEP), and machine-learning / generative approaches - to assess and prioritize targets, identify high-quality starting points, and drive lead optimization toward development candidates.
This is a hands-on, high-impact role on the Antares scientific track. The successful candidate will not only enable programs directly but will also help shape the computational chemistry, machine learning and cheminformatics platform that underpins design across Antares. The role is offered at the Principal or Senior Principal Scientist level; scope, independence, and organizational influence scale with experience, as described under Qualifications.
Key Responsibilities
  • Serve as the computational chemistry function lead on programs, providing integrated leadership across target validation, hit identification, hit-to-lead, and lead optimization for multiple small-molecule programs.
  • Apply structure-based and ligand-based design, molecular dynamics, and free energy perturbation (FEP) to prioritize compounds, evaluate druggability, and identify and exploit cryptic or novel binding pockets on challenging targets.
  • Integrate machine-learning, generative, and active-learning approaches into design-make-test-analyze cycles, and multiparameter optimization of potency, selectivity, and ADMET/physicochemical properties.
  • Partner closely with medicinal chemistry to translate computational hypotheses into synthesized, tested molecules, and to drive sound decision-making and smart risk-taking.
  • Lead computational infrastructure and platform development - identifying, evaluating, and deploying best-in-class tools, methods, and workflows - and contribute to major collaborations with external partners, in coordination with the Discovery Predictive Sciences team.
  • Analyze and integrate data across functions to independently identify, define, and address critical scientific issues and key scientific questions.
  • Communicate analyses, models, and recommendations clearly to project teams and leadership, influencing program strategy and portfolio decisions.
  • Represent computational chemistry in cross-functional program teams; help set design strategy and define the questions that computation should answer at each stage.
  • Mentor junior scientists and, at the Senior Principal level, provide broad scientific direction, establish best practices, and act as a recognized technical authority internally and in the external scientific community.

Qualifications
  • PhD. in computational chemistry, biophysics, theoretical chemistry, pharmaceutical sciences, cheminformatics, or a related quantitative field (or equivalent experience).
  • Principal Scientist: PhD with 10+ years (or bachelor's with 16+ years) of computational chemistry experience in a pharmaceutical and/or biotechnology setting. Senior Principal Scientist: PhD with 12+ years (or bachelor's with 18+ years), with a demonstrated track record of independent scientific leadership, cross-functional influence, and organizational impact.
  • Demonstrated, direct contributions to drug discovery programs through the application of computational chemistry - ideally including progression of compounds into or toward the clinic.
  • Deep, hands-on expertise across modern computational methods: structure- and ligand-based design, molecular dynamics, and free energy methods (e.g., FEP).
  • Experience applying machine-learning and/or generative molecular design methods in a discovery setting is strongly preferred.
  • Experience in covalent drug discovery - including covalent docking, warhead selection and reactivity/selectivity assessment, and modeling of covalent kinetics (e.g., kinact/Ki) - is strongly preferred and is central to Antares' programs.
  • Proficiency with the Schrödinger suite and/or comparable platforms (e.g., MOE, OpenEye), and programming/scripting in Python and with coding assistants like Claude Code/Codex for cheminformatics and data analysis.
  • Strong understanding of medicinal chemistry, structural biology, and DMPK principles, and a proven ability to collaborate effectively in a fast-paced, matrixed, team-based environment.
  • Excellent written and verbal communication skills, with the ability to convey complex computational concepts to multidisciplinary audiences.
  • A passionate, results-oriented drug hunter who thrives in a collaborative, data-driven, and scientifically ambitious culture.

The anticipated annual salary range for this position is $185,000-$240,000 annually. The actual salary offered will be based on a number of factors, including but not limited to the qualifications of the applicant, years of relevant experience, level of education attained, certifications or other professional licenses held, and if applicable, the location in which the applicant lives and/or from which they will be performing the job.

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