Computational Protein Design Scientist (AI/ML)

Basecamp Research • Boston, MA

9h • Onsite

About The Position

At Basecamp Research we're looking for a Computational Protein Design Scientist (AI/ML) to join our team. Full-time · Boston, US About the job Basecamp Research is dedicated to solving major challenges in the life sciences by exploring Beyond Known Biology. Our teams build frontier AI models using BaseData, the world's largest ethically-sourced and globally representative biological dataset. Our Global Research Team collects and curates our own biological data through partnerships with more than 152 organizations in 28 countries, giving its AI access to genetic diversity that doesn't exist for models trained on public database sources. This enables Basecamp Research to design novel protein sequences and biological systems that can accelerate therapeutic research and development. In October 2024 we closed Series B and in January 2026 finalised pre-Series C investment from NVIDIA. With hubs both in London, UK as well as Boston Massachusetts, USA and partners with biopharma companies and academic institutions worldwide, our work has been recognized with honors including Fast Company's Top 10 Most Innovative Companies in Biotech and the FT-backed Sifted AI100 list of Europe's leading AI startups. At Basecamp Research, we pride ourselves on being a diverse, exciting, fun, and flexible place to work. Our team of biologists, engineers, ML scientists, field explorers, and operations specialists are united by a sense of adventure and the belief that nature has already designed the solutions to our planet’s greatest challenges – we just need to go out and discover them! If you feel passionate about the power of biology, data, and AI to build a better world, we’d love to hear from you. About the Role We are seeking a Computational Protein Design Scientist to help develop and apply machine learning methods for AI-Programmable Gene Insertion (aiPGI™). You will work with unusually large and diverse protein-nucleic acid interaction datasets, develop model-driven hypotheses, and partner closely with experimental scientists to validate designs. This role emphasizes practical model evaluation and iteration, not just method development. Prior experience with gene-editing systems is welcome but not required; strong fundamentals in protein modeling and machine learning matter more. The position is based in our Kendall Square office in Cambridge, MA.

Requirements

• Ph.D. in Bioinformatics, Computational Biology, Structural Biology, Biophysics, Computer Science, or a related field.
• Demonstrated research output in protein modeling, protein design, or computational biology (publications, preprints, or equivalent).
• Experience with protein-nucleic acid and/or protein-protein interaction modeling.
• Familiarity with protein language models, generative models, diffusion models, and co-folding models.
• Strong programming skills (Python required; experience with ML frameworks such as PyTorch or JAX preferred).
• Ability to work independently while contributing effectively to multidisciplinary teams.
• Experience translating computational results into biological insight.

Nice To Haves

• Prior industry experience in biotech or pharma.
• Exposure to gene-editing systems (e.g., CRISPR, gene integration, recombinases).

Responsibilities

• Design, implement, and apply modern machine learning and deep learning models for protein discovery and design (e.g., sequence-based, structure-aware, or hybrid approaches).
• Benchmark and critically evaluate models on protein design tasks, including generalization, conditionality, and robustness.
• Analyze and mine large-scale metagenomic and protein datasets to identify novel systems and functional signals.
• Collaborate closely with experimental scientists to translate model outputs into testable designs; and analyze experimental results and iterate on models.
• Communicate results clearly through internal technical presentations, written reports and documentation, as well as data visualizations and summaries

Benefits

• The opportunity to play a key technical role in shaping how AI is applied to protein and gene-editing system development.
• Access to unique, large-scale biological datasets rarely available in academic settings.
• Close collaboration with wet-lab scientists and leading academic partners.
• Competitive salary, equity, comprehensive benefits, and 401(k).
• A fast-moving environment with real ownership and scientific impact.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree