Planet Pharma

Machine Learning Scientist

1 DNA Way South San Francisco, CA 94080 US

Posted: 02/25/2026 2026-02-25 2026-03-27 Employment Type: Contract Job Category: Technology Job Number: 625924 Pay Rate: 51.80 Is job remote?: No Country: United States

Job Description

Machine Learning Scientist (Contract Position)

In the Structure and Simulation team within Prescient Design, we develop modern computational methods to accelerate therapeutic discovery across Genentech Research and Early Development (gRED). Methods we deploy propose new molecules, score designs to prioritize the most promising compounds, generate biological hypotheses through exploratory simulation, accelerate physics-based calculations, and more.

We are seeking a highly motivated Machine Learning Scientist to join our team to develop new scientific methodology and produce and deploy workflows usable by computational and ultimately wet-lab scientists. The successful candidate will collaborate extensively with computational and experimental researchers within Prescient Design and across gRED to advance our scientific understanding of biomolecules.

The Role

• Work as a machine learning scientist to develop new scientific methodology for the understanding, scoring, ranking, generation, and design of biomolecules, especially proteins.
• Work as an engineer of scientific software, to produce usable, deployable code for these new methods to power the lab-in-the-loop.
• Use software best practices (version control, testing, modular code development, documentation, etc.) to collaborate on a large codebase with our team of methods developers.
• Deploy workflows on HPC and cloud platforms and deliver user-friendly web-based interfaces to medicinal chemists across gRED and Roche.

Desired Qualifications

• BS, MS, or PhD degree in a life or physical science or a computational field.
• Expert in Python and experience with scientific software development.
• Experience with deploying software workflows on cloud and/or HPC platforms.
• Experience working on collaborative code bases, including merge requests, code review, writing tests etc.
• Highly-motivated and independent self starter that is eager to collaborate.
• Excellent communication and interpersonal skills.
• Basic understanding of modern machine learning methods including predictive models, generative models, and active learning as applied to molecular generation and optimization.

Additional Qualifications

• Candidates may additionally have, but are not required to have:
• Public portfolio of projects available on GitHub.
• Experience with Rosetta, OpenMM, and/or computational chemistry codes.
• 3+ years of industry experience.
• Extensive experience working with large chemical and biological datasets, including graph, sequence, and structure-based data.

Pay Rate Range: $40-46/hr depending on experience

Equal Opportunity Employer: We are proud to be an equal opportunity employer. We welcome and encourage applications from all qualified candidates regardless of race, sex, gender identity or expression, disability, age, religion or belief, sexual orientation, or any other characteristic protected by applicable laws and regulations. It is our policy not to discriminate against any applicant or employee, and we are committed to fostering a diverse, inclusive, and respectful work environment across all locations in which we operate. We believe that diversity, equity, and inclusion are fundamental to our mission and enhance our ability to serve clients globally. If you have a disability or require any reasonable accommodations during the application or interview process, please inform your recruiter or contact us directly so that we can explore the appropriate arrangements.

Fraud Alert: Candidate safety is a top priority at Planet Pharma. The industry has seen an increase in people falsely representing themselves as recruiters to gather personal information from job seekers. For your safety, do not provide sensitive data to anyone you have not spoken with thoroughly, never provide banking information during the application process and always double check the email address of the Recruiter to ensure it’s from an official Planet Pharma domain (@planet-pharma.com, @planet-pharma.co.uk, and @ppgadvisorypartners.com) and not a domain with an alternative extension like .net, .org or .jobs.

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