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Associate Machine Learning Chemistry Jobs in Washington

GAP Solutions, Inc

Scientist (52632)

Bethesda, MD · On-site

$215K - $228K/yr

... chemistry and structural biology. * Develop new machine learning techniques in response to NIMH researcher needs, in particular in natural language processing for structured prediction problems, the ...

New

GAP SOLUTIONS INC

Scientist (52632)

Bethesda, MD · On-site

... chemistry and structural biology. * Develop new machine learning techniques in response to NIMH researcher needs, in particular in natural language processing for structured prediction problems, the ...

New

GRVTY

Data Scientist 2

Annapolis Junction, MD · On-site

$115K - $145K/yr

This role combines artificial intelligence and machine learning skills with a strong foundation in ... Bachelor's Degree with 3 years of relevant experience or an Associates degree with 5 years of ...

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All JobsAssociate Machine Learning Chemistry JobsAssociate Machine Learning Chemistry Jobs in Washington

Associate Machine Learning Chemistry information

What is an associate machine learning chemistry?

Associate Machine Learning Chemists are professionals who combine expertise in chemistry with skills in machine learning to analyze chemical data, develop predictive models, and accelerate scientific discovery. They often work on tasks like predicting molecular properties, optimizing chemical reactions, and supporting drug discovery efforts using computational tools. Typically, these roles require a strong foundation in chemistry, programming experience (often in Python), and familiarity with machine learning libraries. Associate positions are generally entry-level or early-career roles, providing support to senior scientists and data scientists in research and development teams.

How does an associate machine learning chemistry professional typically collaborate with research scientists and engineers?

As an Associate Machine Learning Chemistry professional, you will frequently work alongside research scientists and chemical engineers to develop predictive models and analyze experimental data. Collaboration involves translating chemical problems into machine learning tasks, sharing insights from model results, and participating in interdisciplinary meetings to refine research objectives. Effective communication and teamwork are essential, as you may be required to explain machine learning concepts to non-technical colleagues and integrate their domain expertise into your models. This collaborative environment fosters both scientific discovery and professional growth.

What are the key skills and qualifications needed to thrive as an associate machine learning chemistry, and why are they important?

To thrive as an Associate Machine Learning Chemistry professional, you need a solid background in chemistry, data analysis, and machine learning, typically supported by a relevant degree such as chemistry, computer science, or a related field. Experience with programming languages like Python, machine learning libraries (e.g., TensorFlow, scikit-learn), and cheminformatics software is highly valued. Strong problem-solving skills, attention to detail, and the ability to communicate complex concepts clearly are crucial soft skills. These competencies enable effective collaboration on interdisciplinary teams and the development of innovative solutions in computational chemistry research.

What is the difference between Associate Machine Learning Chemistry vs Associate Data Scientist?

AspectAssociate Machine Learning ChemistryAssociate Data Scientist
Required CredentialsBachelor's or Master's in Chemistry, Data Science, or related fields; familiarity with ML frameworksBachelor's or Master's in Data Science, Statistics, Computer Science; programming skills in Python/R
Work EnvironmentResearch labs, pharmaceutical or chemical companies, biotech firmsTech companies, finance, healthcare, consulting firms
Employer & Industry UsageUsed in industries applying ML to chemical data, drug discovery, materials scienceApplied across industries analyzing large datasets, predictive modeling

Associate Machine Learning Chemistry focuses on applying machine learning techniques specifically to chemical and scientific data, often within research or pharmaceutical settings. In contrast, Associate Data Scientist has a broader scope, working with various data types across multiple industries. Both roles require strong analytical skills and familiarity with ML tools, but their industry focus and data types differ.

What are the most commonly searched types of Machine Learning Chemistry jobs in Washington?

The most popular types of Machine Learning Chemistry jobs in Washington are:

What are popular job titles related to Associate Machine Learning Chemistry jobs in Washington?

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

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

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

What cities in Washington are hiring for Associate Machine Learning Chemistry jobs?

Cities in Washington with the most Associate Machine Learning Chemistry job openings:

Associate Machine Learning Chemistry jobs near you
Infographic showing various Associate Machine Learning Chemistry job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 84% Physical, 2% Hybrid, and 14% Remote job distribution.

AI Scientist- Computational Chemistry

AIToolboard

Ashburn, VA • On-site

$150 - $200/hr

Other

Posted 20 days ago

Key responsibilities

  • Develop, implement, and execute innovative AI-based research projects related to computational chemistry and biological discoveries.

  • Collaborate with scientists, engineers, and technicians, and coordinate project phases to develop new methods, tools, and research outputs.

  • Apply AI and computational methods to develop chemical and biochemical tools such as fluorescent probes, biosensors, and imaging agents.

Job description

Jobs / AI Scientist- Computational Chemistry

AI Scientist- Computational Chemistry

Full-time

About the Role

About this role:HHMI has made a landmark $500 million commitment to support AI-driven projects and to embed AI systems throughout every stage of the scientific process in labs across HHMI. The AI initiative will be centered at HHMI’s Janelia Research Campus. Janelia has been at the forefront of AI-driven research in biology for more than 15 years. Its forward-thinking structure, centralized funding, and collaborative culture make it ideally suited to take this bold leap forward. To learn more about the initiative, visit ai.hhmi.org.The Artificial Intelligence (AI) Scientist is an outstanding independent scientist who develops, implements, and executes innovative AI-based research projects to make biological discoveries or to generate new research tools. AI Scientists create, lead, or participate in research projects of variable scale, ranging from individual work to HHMI-wide strategic initiatives. The AI Scientist will work closely with scientists from across the broader HHMI community. They participate in, build, or supervise highly collaborative research teams consisting of other scientists, engineers, and technicians.

What We Provide
  • A competitive compensation package with comprehensive health and welfare benefits. In addition to the base salary described below, this position may also be eligible for incentive pay.
  • Generous training and travel opportunities to workshops and conferences.
  • Access to state-of-the-art computational infrastructure and extended capabilities provided through assistance from Janelia’s Support teams and Project teams.
  • A healthy work-life balance, with on‑site childcare, free gyms, on‑campus housing, vibrant social and dining spaces, and shuttle‑bus service to Janelia from Washington, DC metro area!
  • Flexible work arrangements are available.
  • Relocation assistance provided for non‑local candidates who wish to transition to the Washington, DC, metro area.
What You’ll Do
  • Plan, initiate, and rigorously execute independent or collaborative AI-based research; may manage personnel and budgets towards this goal.
  • Plan and perform scientific duties on new and varied problems where only general objectives are stated.
  • Closely collaborate with other scientists, engineers, and technicians.
  • Initiate and remain flexible to transfer between projects and groups as appropriate.
  • Coordinate broad phases of projects and perform advanced development work to obtain and maintain technical leadership in the field of AI.
  • May assist HHMI and Janelia leadership in planning and execution of program‑wide initiatives; ensures coordination with related efforts or other projects and research areas.
  • Provide mentoring and leadership to others.
  • Participate in the review of other projects and scientists and provide input and guidance in a collaborative and constructive way.
  • Explore and develop new methods, skills, and tools. Make research outputs available through peer‑reviewed scientific publications, high‑quality datasets, code, and applications. Participate in patent disclosures where appropriate.
  • Apply AI and computational methods, including generative molecular design, molecular property prediction, and physics‑based simulation, to the development of chemical and biochemical tools such as fluorescent probes, biosensors, and imaging agents, working in close collaboration with experimental chemists and protein engineers.
  • Adhere to the highest academic, scientific, and ethical standards in all professional activities.
What You Bring
  • Ph.D. in Computer Science, AI, Machine Learning, Applied Mathematics, Physics, Chemistry, Chemical Engineering, Computational Chemistry, Biochemistry, Materials Science, or a related field — or equivalent combination of education and experience.
  • Demonstrated record of rigorous, innovative research evidenced by peer‑reviewed publications, high‑quality open‑source contributions, or impactful scientific applications, typically reflecting 5 or more years of research experience.
  • Deep expertise in computational chemistry, molecular photophysics, or a closely related field — including experience with excited‑state property prediction, fluorescent molecule or biosensor design, photoswitches, or related functional molecular systems, and familiarity with quantum chemistry methods (DFT, TD-DFT, or correlated approaches) for predicting photophysical properties such as absorption/emission spectra, quantum yield, and photostability. Candidates with this foundation who are actively building ML capabilities are strongly encouraged to apply.
  • Strong working knowledge of AI/ML methods — including deep learning, probabilistic modeling, and generative or optimization‑based molecular design — with an emphasis on physics‑guided or mechanism‑aware approaches suited to data‑limited chemical domains. Proficiency in PyTorch, JAX, or equivalent frameworks, and strong progr
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