Senior Engineer I/II, Drug Discovery Platform

Lila Sciences
Cambridge
Workplace: OnsiteFull timeUSD 148,000 - 240,000 annuallyFunction: Solutions Engineering & Sales EngineeringExperience: 5+ yearsEducation: bachelorsSkills: []

Own the data backbone for a closed-loop AI drug discovery platform, building the molecule queue, canonical compound/structure registry, and lab instrument data ingestion pipelines. Develop systems for synthesis constraints and inventory so the Batch Assembly AI can execute reliably, while ensuring data quality, lineage, schema evolution, and SLAs to support cycle times of days. Work with backend APIs/services, AWS, and Kubernetes.

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Lila Sciences
Lila Sciences
3 days ago

Senior Engineer I/II, Drug Discovery Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 21 hours agoStatus: Live

Job Summary

Own the data backbone for a closed-loop AI drug discovery platform, building the molecule queue, canonical compound/structure registry, and lab instrument data ingestion pipelines. Develop systems for synthesis constraints and inventory so the Batch Assembly AI can execute reliably, while ensuring data quality, lineage, schema evolution, and SLAs to support cycle times of days. Work with backend APIs/services, AWS, and Kubernetes.
Location: Cambridge
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Design and operate the molecule queue between AI Scientists and the Make-Test platform, including status state machine, batch grouping, and read/write contracts.
  • •Build and maintain a canonical molecule registry with normalization, stereochemistry handling, salt/parent resolution, duplicate detection, and stable internal IDs.
  • •Ingest lab instrument data from ChemSpeed, QC instruments (LCMS, NMR), and bioassay readers, capturing identity, purity, dose-response, IC50/EC50, ADMET, and selectivity into a queryable store.
  • •Maintain synthesis constraints and inventory state for each cycle, including building-block inventory, advanced precursors, ChemSpeed capacity, stock alerts, and chemistry-specific constraints.
  • •Own data quality, lineage, schema evolution, and SLAs for the closed-loop cycle time target from computational proposal to experimental truth.

Pay and Benefits

Salary: USD 148,000 - 240,000 annually
Equity and Bonus:Equity
Perks:Health InsuranceDentalVisionLife InsuranceDisability InsurancePaid ParentalCommuter BenefitsBike ShareMeal Allowance

Key Requirements

  • •Bachelor's or Master's in Computer Science, Chemistry, Computational Biology, or a related field, and 5+ years building data platforms in production, ideally with scientific/lab-generated data exposure.
  • •Designed and shipped data platform components end-to-end (ingestion, registries, storage abstractions, orchestration) and can write production-quality backend APIs/services in Python and SQL.
  • •Production experience with relational and/or NoSQL databases, schema design for evolving scientific data, and query optimization.
  • •Comfortable modeling chemical and biological data (structures, reactions, assays, dose-response, batches) and handling messy experimental measurements (replicates, censored values, failed runs).
  • •Experience with AWS and containerized deployment using Kubernetes.
Experience:5+ yearsDrug discoveryBiotechPharmaData platformsScientific data
Education:Bachelor's
Languages:English
Tech Stack:PythonSQLAWSKubernetesRDKitOpenEyeSMILESInChIChemSpeedLCMSNMRBioassay readersFlyteAirflowDagsterTemporalIcebergDelta LakeHudiDuckDB

Company Brief

Lila Sciences
Develops AI-driven platforms to accelerate drug discovery and biological research by integrating machine learning with chemical and biological data to predict molecular properties, streamline candidate selection, and enable faster therapeutic development.
Industry: Biotech
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
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