
Frontier Medicines is a precision medicine company that has pioneered a proprietary discovery and development platform to develop medicines against disease-causing proteins previously considered undruggable. They utilize groundbreaking scientific approaches in chemoproteomics, covalent drug discovery, and machine learning to create innovative therapies, particularly in oncology. Their lead program, FMC-376, targets KRASG12C mutations prevalent in various cancers. Frontier's collaboration with AbbVie aims to develop novel therapies against challenging protein targets, significantly broadening the therapeutic landscape.

Frontier Medicines is a precision medicine company that has pioneered a proprietary discovery and development platform to develop medicines against disease-causing proteins previously considered undruggable. They utilize groundbreaking scientific approaches in chemoproteomics, covalent drug discovery, and machine learning to create innovative therapies, particularly in oncology. Their lead program, FMC-376, targets KRASG12C mutations prevalent in various cancers. Frontier's collaboration with AbbVie aims to develop novel therapies against challenging protein targets, significantly broadening the therapeutic landscape.
Sector: Biotechnology Research — precision small-molecule therapeutics
Platform: Frontier™ platform: chemoproteomics + covalent discovery + machine learning
Lead programs: FMC-376 (KRASG12C, clinical) and FMC-220 (p53 Y220C, preclinical)
Founded: 2018
Known funding (total reported): USD 255,500,000
Offices: South San Francisco and Boston
Targeting previously undruggable, disease-causing proteins in oncology via covalent small-molecule approaches.
2018
Biotechnology Research
67000000 USD
88500000 USD
80000000 USD
Reported as oversubscribed; included strategic investor participation
“Backed by venture and crossover investors including Deerfield Management, RA Capital, Woodline Partners, MPM Capital, Droia Ventures, DCVC Bio, RA Capital Management, Galapagos, ArrowMark Partners and others”
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Frontier Medicines is seeking a highly motivated Scientist, AI Cheminformatics to join our Machine Learning organization. This role will play a key scientific and technical role in advancing Frontier's AI and cheminformatics capabilities in support of covalent small molecule drug discovery.
The successful candidate will design and implement machine learning, cheminformatics, and advanced analytics workflows that leverage Frontier's large scale covalent chemistry data to guide covalent compound design, prioritization, and optimization. This role works closely with medicinal chemistry, biology, and cross-functional drug discovery teams to translate complex data into actionable insights.
This position is ideal for an individual contributor who thrives in scientifically uncharted territory and enjoys building novel solutions where no template exists and loves to enable others through their work.
This is an exciting opportunity in our South San Francisco site to deploy AI to make a difference for patients suffering from debilitating diseases by working in a highly collaborative and energetic team in a startup environment with short communication lines across functions and departments
What will you be doing?
Design, develop, and apply cheminformatics and AI workflows to support small molecule discovery, including compound prioritization, library design, and structure-activity relationship analysis
Develop and deploy machine learning models using proprietary chemoproteomics, chemistry, and experimental datasets to drive biological insight and project decision-making.
Partner closely with medicinal chemistry and drug discovery teams as an embedded analytics and AI expert, act as a liaison to the computational and medicinal chemistry departments and project teams.
Design novel algorithms and analytical approaches tailored to Frontier's unique datasets and scientific questions.
Stay current with emerging advances in AI, cheminformatics, and computational drug discovery, and lead internal adoption of promising methods.
Communicate results, hypotheses, and recommendations clearly through presentations, documentation, and scientific discussions.
Contribute to scalable, maintainable, and reproducible software and analytics solutions following best practices.
Requirements
Traits we believe make a strong candidate:
PhD in computational or quantitative discipline such as cheminformatics, computational chemistry, computer science, data science, computational biology, chemical engineering, or a related field.
Strong programming skills in Python
Experience applying AI to medicinal chemistry or cheminformatics problems (e.g., molecular representations, fingerprints, generative models, transformers, pretraining strategies, property prediction, virtual screening, ADMET modeling)
Comfort with modern software development practices including version control, testing, containerization, and cloud-based computing environments (AWS experience is a plus).
Ability to work independently while thriving in a highly collaborative, cross-functional environment.
Excellent written and verbal communication skills.
Legally authorized to work in the United States.
Leveling Guidelines
Scientist
Minimum 1+ years of relevant industry experience.
Demonstrated ability to independently or with limited guidance design and execute computational and AI approaches for drug discovery problems.
Proven track record of leading complex analytical strategies and influencing discovery programs through data-driven insights.
Ability to effectively collaborate with experts from other domains
Benefits
At Frontier, we strive to build a diverse and equitable workplace. The salary range for this role is $130,000 - $175,000. Compensation for the role will depend on a number of factors, including candidates' qualifications, skills, competencies and experience. Frontier offers a competitive total rewards package which includes healthcare coverage, 401k and a broad range of other benefits.
This compensation and benefits information is based on Frontier's knowledge as of the date of publication, and may be modified in the future.