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About the Role
Lila’s mission is to accelerate scientific discovery with AI, and that depends on trustworthy scientific data. As a Data Engineer, you’ll build ETL pipelines and data models for Lila’s scientific data platform, working at the intersection of data engineering, computational biology, chemistry, and materials science. You’ll partner with AI researchers and experimentalists to turn raw lab instrument outputs into validated, analysis-ready datasets. The core challenge is data modeling: transforming messy, per-instrument measurements into clean, well-typed data that is efficient to query, reliable to use, and ready for downstream analysis. You’ll also build domain-specific analysis functions and reusable data pipelines that help scientists and AI researchers move faster without re-deriving bespoke solutions.
Responsibilities
- Design pipelines that turn raw lab output into analysis-ready scientific data.
- Model heterogeneous data from bio, chemistry, and materials instruments.
- Build validation checks, schema-evolution gates, and data quality workflows.
- Develop reusable analysis functions for scientific and AI research workflows.
- Improve automation and observability across instrument-to-result data flows.
- Build canonical datasets that scientists and AI researchers can trust.
- Use AI coding tools to accelerate pipeline development and team velocity.
Requirements
- 2–6 years of experience in data engineering, bioinformatics, cheminformatics, or computational science.
- Strong Python skills, including typed, tested, production-quality code.
- Strong SQL skills, especially with Postgres or similar relational databases.
- Experience building ETL pipelines, data models, and reusable data transformations.
- Data science foundation, including statistics and pandas, NumPy, or similar tools.
- Experience translating noisy scientific measurements into accurate, validated datasets.
- Workflow orchestration experience, ideally Flyte, Airflow, Prefect, Dagster, or Nextflow.
- Active use of AI coding tools in day-to-day engineering work.
Skills
- Python
- SQL
- Postgres
- ETL pipelines
- Data models
- Data transformations
- Statistics
- Pandas
- NumPy
- Workflow orchestration
- Flyte
- Airflow
- Prefect
- Dagster
- Nextflow
- AI coding tools
- Parquet
- Iceberg
- DuckDB
- Polars
- Ibis
- NATS
- Kafka
- LIMS
- ELN systems
- XRD
- XRF
- SEM
- TGA
- DSC
- Curve fitting
- Peak detection
- Unit and dimensional analysis
Work Type
- Full-time
Experience Level
- 2-6 years
Salary/Compensations
- $144,000—$240,000 USD
Benefits
- Competitive base compensation with bonus potential and 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.
- International benefits tailored to their region.
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.
- Learn more at www.lila.ai.
- 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.