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About the Role
Lila is building an operating system for science, powered by scientific superintelligence. The Molecular Intelligence team builds ML and physics-based infrastructure for drug discovery. This role sits embedded with scientists, working closely with Lila’s platform teams on the storage, compute, and orchestration layers. You’ll build the provenance system that connects every scientific input, code version, model, run, and result produced across Lila’s simulation, ML, and agent-driven workflows.
Responsibilities
- Build shared provenance infrastructure — a queryable, trusted record connecting inputs, code/model versions, runs, and outputs across simulation, ML, and agent workflows.
- Develop data models and metadata schemas for runs, artifacts, and results that work across heterogeneous scientific tools.
- Create reusable Python libraries and APIs that let tools, pipelines, and AI agents write to and read from shared storage and metadata systems.
- Generate structured records from agent activity — turning ephemeral agent traces into durable, queryable data.
- Develop production-grade tooling from research prototypes — taking scientific workflows from one-off scripts to scalable, maintainable services.
- Establish engineering conventions (CI, testing, packaging, release practices, documentation) that hold up across local, cloud, and GPU compute environments.
Requirements
- Strong Python engineering skills with a track record of designing and shipping maintainable systems.
- Experience with data modeling — schemas, metadata, identifiers, versioning for data that changes over time.
- Experience designing APIs and building libraries that other engineers or scientists depend on.
- Experience supporting research workflows (ML experiments, simulations, data pipelines) with a clear sense of what makes results reproducible.
Skills
- Python
- Data modeling
- API design
- Library development
- Reproducibility
- Chemistry
- Computational biophysics
- Molecular simulation
- Drug discovery workflows
- Experiment tracking
- Data lineage
- MLflow
- Weights & Biases
- OpenLineage
- DVC
- Workflow orchestration
- Flyte
- Ray
- Argo
- Airflow
- Temporal
- Dagster
- Kubernetes
- Containers
- CI/CD
- GPU computing
- LLM agents
- Automated research workflows
Location
- U.S.
Work Type
- Full-time
Salary/Compensations
- $148,000—$240,000 USD
Benefits
- Competitive base compensation with bonus potential
- Generous early-stage equity
- Medical, dental, and vision coverage
- Employer-paid life and disability insurance
- Flexible time off with generous company wide holidays
- Paid parental leave
- Educational assistance program
- Commuter benefits, including bike share memberships for office based employees
- Company subsidized lunch program
About the Company
- Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges.
- We believe science is the most inspiring frontier for AI.
- Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.
- LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy.
- Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance.
Equal Opportunity
- Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.