Principal ML Research Engineer
On-site · San Francisco, California, United States
Job Summary
Principal ML Research Engineer to lead the founding engineering effort for an autonomous-science cell-biology platform. Build and operate the domain data platform (data curation, lineage, schema, versioning for multi-modal data such as single-cell, multi-omics, spatial, imaging, perturbation, genetics); deploy and maintain a shared specialist-model serving and fine-tuning stack; establish the cross-program evaluation harness and agentic infrastructure (rollout generation, tool orchestration, rubric grading, trace-QC); integrate with Lila's central AI/Data platforms; co-develop platform strategy with team leads; set engineering standards, champion reproducibility and deployment hygiene, mentor engineers, and represent the platform externally via open-source contributions and conferences.
Required Qualifications
- Advanced degree in Computer Science, Machine Learning, Engineering, or related quantitative field, or equivalent industry track record
- 8+ years of ML platform, infrastructure, or research-engineering experience with a track record of shipping/operating production ML systems
- Hands-on ML platform building experience (model serving, fine-tuning and training pipelines, agentic orchestration, evaluation harnesses, data pipelines)
- Domain data engineering depth (designing and operating data pipelines for high-dimensional multi-modal scientific data)
- Experience with specialist-model serving, fine-tuning, and integration for heterogeneous models
- Experience with agentic/autonomous-science systems (closed-loop, tool orchestration, experiments planning)
- Proficiency in PyTorch (or JAX/TensorFlow), large-scale data loading, inference-time optimization; strong software engineering (Python, containers, Kubernetes, CI/CD, IaC)
- Cross-functional collaboration across ML scientists, computational biologists, experimental scientists, and platform teams
- Willingness to contribute to open-source and engage in external conferences/recruiting
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