Scientific Software Engineer – AI & Lab Automation

BioSpace; San Francisco (CA); On-site; USD 152,000 - 244,000; Full time

Benefits offered by this job

401(k) plan

Medical, dental, vision benefits

Pension

Vacation benefits

Flexible benefits

Life insurance

Employee clubs

Job summary

Lilly is seeking a Scientific Software Developer to build software powering AI-native drug discovery. You will work directly with discovery scientists to translate needs into prototypes, data pipelines, APIs, ML tooling, and lab automation integrations across Architecture4Insight, Methods4Insight, and Automation & Scale4Insight.

This role centers on rapid prototyping, cloud-native infrastructure, and handoffs to Tech@Lilly for enterprise scaling.

Qualifications

• BS/MS/PhD in CS/biomedical fields with 5+ years of software work.
• Strong Python and SQL skills; experience in APIs and data pipelines.
• Experience building RESTful APIs, microservices or related infra.
• Experience in pharma/biotech discovery workflows is a plus.

Responsibilities

• Design, build, and maintain data pipelines for complex datasets, ensuring FAIR data.
• Develop RESTful APIs and microservices for LIMS, ELNs, instruments, and data warehouses.
• Operationalize cheminformatics and AI/ML models as production APIs.
• Integrate lab automation systems with digital platforms and Data Foundry infra.
• Prototype dashboards/tools for scientists and hand off to Tech@Lilly for scaling.

Skills

Python

SQL

RESTful APIs

Data pipelines

ML/AI tooling

Cloud platforms

Docker/Kubernetes

LIMS/ELN

CI/CD

Cheminformatics

Education

B.S./M.S./PhD in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, Chemistry, Biology, Biomedical Engineering, or related STEM field

Tools

RDKit

Schrödinger

MOE

PostgreSQL

Redshift

Snowflake

BigQuery

Benchling

Docker

Kubernetes

Prefect

Airflow

Nextflow

Job description

Lilly is seeking a Scientific Software Developer to build software powering AI-native drug discovery. You will work directly with discovery scientists to translate needs into prototypes, data pipelines, APIs, ML tooling, and lab automation integrations across Architecture4Insight, Methods4Insight, and Automation & Scale4Insight.

This role centers on rapid prototyping, cloud-native infrastructure, and handoffs to Tech@Lilly for enterprise scaling.