Lila Sciences
Research Engineer, Scientific Data & Workflow Infrastructure
$148K–$240K
Cambridge, MA USA +2 · Full-time · Posted Aug 3, 2026
- Location
- Cambridge, MA USA
San Francisco, CA USA
Alewife, Cambridge, MA
About the job
Build provenance, data modeling, and workflow infrastructure that makes scientific simulation, ML, and agent-driven results traceable, reusable, and reproducible.
What you'll do
- Develop shared provenance systems, metadata schemas, and APIs for scientific inputs, code and model versions, runs, artifacts, and results.
- Turn agent activity into durable, queryable records and research prototypes into scalable, maintainable services.
- Establish engineering practices for testing, packaging, releases, and documentation across local, cloud, and GPU environments.
What they ask for
- Strong Python engineering skills and a track record of designing and shipping maintainable systems.
- Experience with data modeling, including schemas, metadata, identifiers, and versioning.
- Experience designing APIs and building libraries for other engineers or scientists.
- Experience supporting research workflows and understanding reproducibility.
Nice to have
- Familiarity with chemistry, computational biophysics, molecular simulation, or drug discovery workflows.
- Experience with lineage or workflow tools, Kubernetes, CI/CD, GPU computing, or tools for LLM agents and automated research.
Pay
$148,000 — $240,000 USD (base salary)
Tools
Python, MLflow, Weights & Biases, OpenLineage, DVC, Flyte, Ray, Argo
AI focus
Build infrastructure that supports AI agents in scientific workflows, including APIs and shared storage for agent access and durable records of agent activity.
Model-written summary · the original posting is authoritative