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Machine Learning Computational Chemistry Jobs (NOW HIRING)

Pfizer, Inc.

Senior Computational Chemist

La Jolla, CA · On-site

$106K - $176K/yr

Position Summary The Machine Learning & Computational Sciences (MLCS) organization within Medicine ... MLCS supports medicinal chemistry and drug design teams by enabling data-driven decision making ...

Pfizer

Senior Computational Chemist

La Jolla, CA · On-site +1

$106K - $176K/yr

Position Summary The Machine Learning & Computational Sciences (MLCS) organization within Medicine ... MLCS supports medicinal chemistry and drug design teams by enabling data-driven decision making ...

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 Computational Chemistry information

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$24.5K

$114.5K

$211.5K

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

As of Aug 12, 2026, the average yearly pay for machine learning computational chemistry in the United States is $114,469.00, according to ZipRecruiter salary data. Most workers in this role earn between $77,000.00 and $154,500.00 per year, depending on experience, location, and employer.

Is computational chemistry in demand?

Computational chemistry is in high demand within industries such as pharmaceuticals, materials science, and chemical research, where it supports drug discovery and molecular modeling. Professionals with skills in machine learning, programming, and chemistry are increasingly sought after to develop advanced simulation tools and analyze complex data sets.

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 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.
More about Machine Learning Computational Chemistry jobs
What cities are hiring for Machine Learning Computational Chemistry jobs? Cities with the most Machine Learning Computational Chemistry job openings:
What states have the most Machine Learning Computational Chemistry jobs? States with the most job openings for Machine Learning Computational Chemistry jobs include:
What job categories do people searching Machine Learning Computational Chemistry jobs look for? The top searched job categories for Machine Learning Computational Chemistry jobs are:
Machine Learning Computational Chemistry jobs near you
Infographic showing various Machine Learning Computational Chemistry job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $114,469 per year, or $55 per hour.

Associate Director/Director, Alliance Management - AI Discovery

Iambic Therapeutics, Inc

Remote

$155K - $240K/yr

Full-time

Medical, Life, Retirement, PTO

Posted 21 days ago

Job description

JOB SUMMARY
We are seeking an experienced Associate Director or Director of Alliance Management to support AI discovery collaborations. In this role, you will serve as the primary relationship lead for external partnerships, contribute operationally to collaborations, and work closely with other leaders in Iambic to ensure that collaborations advance scientific, operational, and strategic objectives.
You will coordinate cross-functional teams across machine learning, computational chemistry, biology, software engineering, legal, and business development while serving as a trusted partner to pharmaceutical and biotechnology collaborators. Success in this role requires exceptional program leadership and relationship management, together with the ability to translate complex scientific goals into well-executed collaborative projects.
We will prefer candidates who can work onsite at our SD Headquarters, but we are open to hybrid working models and remote US-based applicants.
KEY RESPONSIBILITIES
  • Serve as the primary alliance manager for AI-enabled drug discovery collaborations and strategic external partnerships.
  • Build and maintain trusted relationships with pharmaceutical, biotechnology, and technology partners across scientific, operational, and executive levels.
  • Lead collaboration governance, including Joint Steering Committees (JSCs), scientific working groups, executive reviews, agendas, action tracking, and decision documentation.
  • Partner with Discovery Machine Learning, Computational Chemistry, Biology, Medicinal Chemistry, Software Engineering, Legal, Business Development, and other cross-functional teams to ensure alignment on collaboration objectives, milestones, and deliverables.
  • Develop and maintain integrated collaboration plans, including timelines, governance milestones, partner commitments, contractual obligations, budgets, and partnership metrics.
  • Coordinate cross-functional execution across multiple partnered programs by proactively identifying risks, tracking dependencies, facilitating issue resolution, and ensuring operational excellence.
  • Translate complex AI, machine learning, computational chemistry, and scientific concepts into clear, actionable updates for external collaborators while ensuring alignment between technical teams and partner objectives.
  • Develop sufficient technical understanding of Iambic's AI discovery platform and computational workflows to effectively represent collaborative programs, anticipate partner questions, and facilitate productive scientific discussions.
  • Partner with Legal and Business Development to support collaboration agreements, governance structures, data sharing, publications, and strategic partnership activities.
  • Prepare executive updates, partnership reports, and presentations while contributing to evaluation and launch of new strategic collaborations.
  • Help establish and continuously improve alliance management processes, governance standards, and best practices as Iambic's collaboration portfolio grows.

QUALIFICATIONS
  • Bachelor's degree in a scientific discipline, engineering, business, or related field; advanced degree (M.S. or Ph.D.) preferred
  • 10+ years of experience (Associate Director) or 12+ years (Director) in alliance management, scientific program management, project management, or scientific operations within biotechnology, pharmaceuticals, or AI-driven life sciences.
  • Experience managing complex scientific collaborations and strategic partnerships.
  • Understanding of drug discovery, machine learning, or computational research environments.
  • Exceptional organizational, communication, and stakeholder management skills.
  • Proven ability to influence across multidisciplinary teams without direct authority.

Preferred
  • Experience supporting AI, machine learning, computational biology, computational chemistry, or AI-enabled drug discovery organizations.
  • Experience working with pharmaceutical, biotechnology, academic, or technology collaborations.
  • Familiarity with collaboration agreements, governance structures, and cross-company research programs.
  • Alliance Management (ASAP), PMP, or similar certification.

ABOUT IAMBIC THERAPEUTICS
Iambic is a clinical-stage life-science and technology company developing novel medicines using its AI-driven discovery and development platform. Based in San Diego and founded in 2020, Iambic has assembled a world-class team that unites pioneering AI experts and experienced drug hunters. The Iambic platform has demonstrated delivery of new drug candidates to human clinical trials with unprecedented speed and across multiple target classes and mechanisms of action. Iambic is advancing a pipeline of potential best-in-class and first-in-class clinical assets, both internally and in partnership, to address urgent unmet patient need. Learn more about the Iambic team, platform, pipeline, and partnerships at iambic.ai.
MISSION & CORE VALUES
Our mission is to deliver better medicines through innovations in AI-based discovery technologies. The culture and work at Iambic Therapeutics are profoundly strengthened by the diversity of our people and our differences in background, culture, national origin, religion, sexual orientation, and life experiences. We are committed to building an inclusive environment where a diverse group of talented humans work together to discover therapeutics and create technologies.
PAY AND BENEFITS
We offer industry leading competitive pay, company paid healthcare, flexible spending accounts, voluntary life insurance, 401K matching, and uncapped vacation to our team. We are in a brand-new state-of-the art facility in beautiful San Diego with an onsite gym, dining, and easy access to great places to live and play.

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