Research Engineer, Scientific Data & Workflow Infrastructure
Lila Sciences26 days ago
Base Salary
$148k - $240k/yr
Responsibilities
- Build shared, queryable provenance infrastructure connecting scientific inputs, code and model versions, runs, and outputs.
- Design data models and metadata schemas for scientific runs, artifacts, and results across heterogeneous tools.
- Develop reusable Python libraries and APIs for tools, pipelines, and AI agents to access shared storage and metadata systems.
- Convert agent activity traces into durable, queryable records.
- Turn research prototypes and one-off scripts into scalable, maintainable production services.
- Establish engineering conventions for CI, testing, packaging, releases, and documentation across local, cloud, and GPU environments.
- Work closely with scientists and platform teams on storage, compute, and workflow orchestration infrastructure.
Requirements
- Strong Python engineering skills and a track record of designing and shipping maintainable systems.
- Experience with data modeling, including schemas, metadata, identifiers, and versioning for changing data.
- Experience designing APIs and building libraries used by engineers or scientists.
- Experience supporting ML experiments, simulations, or data pipelines with an emphasis on reproducibility.
- Preferred experience with chemistry, computational biophysics, molecular simulation, or drug discovery workflows.
- Preferred experience with experiment tracking or data lineage tools such as MLflow, Weights & Biases, OpenLineage, or DVC.
- Preferred experience with workflow orchestration tools such as Flyte, Ray, Argo, Airflow, Temporal, or Dagster.
- Preferred experience with Kubernetes, containers, and CI/CD at scale.
- Preferred GPU computing experience at hundreds-to-thousands-of-GPU scale.
- Preferred experience building tools for LLM agents or automated research workflows.
Benefits
- Full-time U.S. employees receive medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off; generous company-wide holidays; paid parental leave; educational assistance; commuter benefits including bike share memberships for office-based employees; and a company-subsidized lunch program.
- Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region.
- Competitive base compensation, bonus potential, and generous early-stage equity are offered.
- International salaries are set to local market, and stated USD salary ranges apply only to U.S.-based positions.
Tech Stack
Categories
BackendData Engineering
About Lila Sciences
Lila Sciences builds an AI-driven research platform and autonomous lab systems for life science, chemistry, and materials R&D teams. Its products combine large AI models with robotic instruments to plan, run, and analyze experiments, integrating into customer-specific scientific workflows. The privately held company serves pharma, materials, and energy organizations and is venture-backed, including a Series A financing in 2025.