Principal ML Research Engineer

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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Mental health support

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Relocation assistance

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401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Principal From the posting source checked Jun 20, 2026

Schedule

Shift type

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Weekend work

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Application

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Assessment

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Deadline

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Where they hire

State eligibility is not yet verified.

About this role

Principal ML Research Engineer San Francisco, CA USA Your Impact at LILA Lila is building a platform where AI and automation co-evolve to solve the hardest problems in science. Within Life Science AI (LSAI), we are launching a new AI for Cell Biology team to develop autonomous-science capabilities for cellular and tissue biology, spanning single-cell omics, perturbation biology, spatial profiling, imaging, genetics, and multi-modal experimental data; that integrate deep biological expertise with foundation modeling and agentic systems. We are seeking a Principal ML Research Engineer to be the founding engineering leader on this team . This is a 0→1 hands-on role. You will build and operate the engineering platform : domain data, domain-specific models, shared specialist-model serving and inference, agentic infrastructure, and the evaluation harness that the team's research programs run on, and that integrates cell-biology research with Lila's central autonomous-science platform: it's core-model, agentic-systems, and experimental-automation infrastructure that closes the loop between AI reasoning and the lab. You will work closely with Lila's central AI Platform, Data Platform, and autonomous-lab engineering teams to leverage and extend core Lila infrastructure rather than rebuild it , and you will co-develop the technical direction of the team with the VP of AI for Cell Biology and its ML Scientists as you build. Cell- and tissue-scale biology sits at an open frontier of AI for science. The field has produced strong specialist models across sub-domains: single-cell foundation models, molecular structural prediction, perturbation response, cellular imaging, pathway and ligand-receptor inference - but the engineering

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