Co-Op, LS AI, ML Scientist for Protein Engineering
Lila Sciences · San Francisco, CA
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Jun 29, 2026
San Francisco, CA
Jul 21, 2026
What this job asks for AI summary
A co-op position for a PhD student to conduct applied machine learning research in protein engineering. Day-to-day work involves building and evaluating generative and predictive models for protein sequence, structure, and developability, analyzing biological datasets, and prototyping computational workflows that incorporate feedback from wet-lab experiments. The role suits candidates with an ML research background who want hands-on experience at the intersection of AI and biology.
Junior level · National · Internship
“or” means any one of them counts — you don't need all of them.
Posted 2 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $122,874 (middle half $87,544–$162,374).
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (8)
This is a Co-Op (cooperative education internship) role explicitly requiring current PhD enrollment — classified as Internship accordingly.
No work location or city is stated in the posting; CBSA is left blank. The company (Lila Sciences) is based in the Boston, MA area but the JD does not specify a location for this role.
The role sits at the boundary between Data Science (ML modeling, generative models, biological datasets) and Software Development (prototyping workflows, ML frameworks); 15-2051 was chosen as primary given the research/modeling emphasis, with 15-1252 as the runner-up.
The degree requirement field is set to None because the JD requires current PhD enrollment rather than a completed degree — it is a student co-op position.
PyTorch is listed as the primary ML framework with JAX as an explicitly named alternative ('PyTorch, JAX, or similar'); both are captured on one skill entry.
Protein language models, structure prediction, diffusion/flow-based models, and active learning appear only under the 'Bonus Points For' section and are therefore preferred, not required.
No compensation figures are provided in the posting.
Posting is for a internship engagement — the market benchmarks below price full-time roles, so read the comp comparison with that in mind.
Read the full posting
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