Automation Engineer - Scientific Data, AI/ML Pipelines & Integration Dev
Core
Build robust data components, scientific system integrations, and AI-enabled insights by translating experimental workflows into scalable software solutions for life sciences R&D.
Role type
Senior IC Automation Engineer (Scientific Data & AI/ML Pipelines)
Builds
Python-based backend services, APIs, microservices, and data pipelines on AWS integrating with scientific systems like Benchling, LIMS, and ELN.
Domain
Life Sciences / Biotechnology / Pharmaceutical Informatics
Deliverable
production ML models | product features | infrastructure
Required skills
Python (FastAPI), SQL/NoSQL database design, AWS cloud services, CI/CD pipeline implementation, scientific data modeling, ETL/ELT development, Docker containerization, REST API design, Test-Driven Development, Git version control.
Preferred skills
Experience with Benchling or similar scientific platforms, AI/ML concepts (feature engineering, model integration), TensorFlow/PyTorch, Agile/Scrum methodologies.
Technologies
Python, FastAPI, AWS (S3, EC2, Lambda, Step Functions, RDS/Aurora), PostgreSQL, MySQL, DynamoDB, MongoDB, Docker, Git, JIRA, Confluence, Benchling, LIMS, ELN, SDMS, pandas, NumPy, scikit-learn.
Responsibilities
Collaborate with scientists to capture end-to-end assay workflows; Design and optimize data models for high-volume scientific data; Develop and maintain backend services and data pipelines; Implement CI/CD pipelines for automated deployment; Ensure solutions meet regulatory compliance (GxP, 21 CFR Part 11); Perform code reviews and debugging.
Seniority
Mid-Senior, hands-on IC
