Scientific Software Developers
Role details
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Tech stack
Job description
We are seeking Scientific Software Developers at multiple levels to build the data infrastructure, scientific tools, and lab automation integrations that power AI-native drug discovery. You will work directly with front-line discovery scientists and data scientists to translate their needs into fit-for-purpose prototypes, data pipelines, APIs, and workflow tools-then hand off mature solutions to Tech@Lilly for enterprise scaling and maintenance if and when needed.
This role is anchored in Architecture4Insight with close collaboration across Methods4Insight and Automation & Scale4Insight. You will build the scientific software that other teams-including the Frontier AI group's autonomous agents-consume. Some developers will specialize in lab automation software: building the code that interfaces with physical instruments, robotic platforms, and scheduling systems to enable Scale4Insight's closed-loop experimentation. ResponsibilitiesScientific Data Pipelines & APIs
- Design, build, and maintain data processing pipelines for complex scientific datasets (chemical, biological, High throughput experiments, and automation-generated data), ensuring FAIR compliance and machine-actionability.
- Develop RESTful APIs and microservices providing unified programmatic access to LIMS, ELNs, instruments, data warehouses (Postgres, Redshift, Snowflake), and analytical databases.
- Support continuous improvement of LIMS and adjacent systems to meet evolving scientific workflows, security, and scalability standards.
Scientific Prototyping & Tech@Lilly Handoff
- Work directly with bench scientists to understand pain points and rapidly prototype custom applications, dashboards, and workflow tools.
- Validate prototypes through iterative scientist feedback, ensuring solutions are fit-for-purpose before transition.
- Partner with Tech@Lilly Product Engineering to hand off mature prototypes for enterprise scaling, defining transition criteria, documentation standards, and SLAs.
Automation Software & Lab Integration
- Build integrations connecting lab automation equipment, scheduling systems, and instrument data streams to Data Foundry's infrastructure with proper metadata and execution traceability.
- Develop software for robotic workflow control, instrument driver interfaces, and real-time data capture from automated platforms.
- Create modular, reusable automation workflow components scientists can configure without writing code.
- Support Scale4Insight's Agentic Lab by building software enabling seamless interfacing between automation platforms and AI-driven experimental planning.
Cloud Infrastructure & DevSecOps
- Build and operate cloud-native components (AWS, Azure, or GCP) supporting containerized workflows (Kubernetes/Docker), infrastructure-as-code, CI/CD, and workflow orchestration (Prefect, Airflow, Nextflow).
- Apply DevSecOps standards including security scanning, code review, and automated testing.
- Participate in agile development with iterative improvement and cross-functional collaboration., The Mailroom Lead supervises processing and delivery of mail, manages staff schedules, solves complex shipping issues, and ensures adherence to procedures. Top Skills: Google SuiteMicrosoft Office Suite SoFi
Mailroom Associate
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Requirements
- B.S. or M.S. in Computer Science, Bioinformatics, Cheminformatics, Computational Biology, Chemistry, Biology, Biomedical Engineering, or related STEM field.
- Bachelor with 3+ years and Master with 1+ years of scientific software development, with understanding of experimental data types and scientific workflows.
- Proficiency in Python and at least one additional language (Java, C#, Go, or TypeScript); SQL skills appropriate to level.
- Qualified applicants must be authorized to work in the United States on a full-time basis. Lilly will not provide support for or sponsor work authorization or visas for this role, including but not limited to F-1 CPT, F-1 OPT, F-1 STEM OPT, J-1, H-1B, TN, O-1, E-3, H-1B1, or L-1., * Experience (or demonstrated aptitude at junior levels) building RESTful APIs, data pipelines, and/or microservices for scientific or technical applications.
- Familiarity with cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and Git.
- Strong communication skills and interest to collaborate with scientists and multi-functional teams.
- Pharmaceutical or biotech research industry experience, particularly in discovery workflows for biology, chemistry, or automation.
- LIMS/ELN experience (e.g., Benchling) and laboratory instrument integration.
- Experience integrating lab automation systems with digital platforms, including instrument control, robotic workflow orchestration, or scheduling systems (OPC-UA, serial/USB protocols, automation scheduling platforms).
- Data warehousing experience (Postgres, Redshift, BigQuery, Snowflake) and scientific data standards/ontologies.
- Hands-on experience with cheminformatics tools (RDKit, Schrödinger, MOE) or bioinformatics platforms (Biopython, Bioconductor, sequence analysis pipelines).
- Experience with scientific computing libraries (SciPy, NumPy) for numerical methods, ODE solvers, optimization, or PK/PD modeling workflows.
- Workflow orchestration (Prefect, Airflow, Nextflow, WDL) and CI/CD practices.
- Strong learning agility-willingness to step outside comfort zone and adopt new technologies to get the job done.
- Experience with C, C++, or other compiled languages for porting performance-critical scientific workflows; ability to profile and identify computational bottlenecks.
Benefits & conditions
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