Lila Sciences
AI
StaffSoftwareEngineer,ScientificSystemofRecord
“Staff Software Engineer, Scientific System of Record at Lila Sciences. Skills: front-end engineering, backend engineering, data modeling, system design. Develop user interfaces. Develop services”
What You'll Achieve.
handle diverse workloads; scale seamlessly; ensure reproducibility; close the Design-Build-Test-Learn loop; improve engineering productivity
Industry & Context.
take ownership of complex technical challenges; balancing trade-offs between scalability, performance, and maintainability
What They're Looking For.
Must Have
Bachelor’s or Master’s degree in Computer Science, Engineering, or related field, 6–8+ years of engineering experience building and deploying large-scale systems in production, expertise in at least one of the following areas, with the ability to work across the stack: front-end engineering, backend engineering, or data modeling and system design, TypeScript, React, Python, SQL, NoSQL, vector databases, schema design, indexing, query optimization, RESTful APIs, GraphQL APIs, AI coding assistants, life sciences, materials science, research-heavy or data-intensive fields, Communication, Collaboration, listening skills, Problem Solving, ownership of complex technical challenges
Nice to Have
Python experience is strongly preferred, Hands-on experience using AI coding assistants to improve engineering productivity, AWS, GCP, Kubernetes, containerization, infrastructure as code, Terraform, CloudFormation, CI/CD pipelines, GitHub Actions, Flyte, Temporal, Airflow, Prefect, laboratory, scientific workflow, LIMS, ELN, data platform, ML platform products, auditability, traceability, reproducibility, data provenance, regulated workflows
What You'll Do.
Develop user interfaces
Develop high-performance APIs
Develop reliable systems
Integrate AI frameworks
Integrate scientific analytics
Integrate laboratory workflows
Drive application development
Diagnose system bottlenecks
Ensure high availability
Ensure low-latency performance
Leverage AWS services
Leverage DevOps practices
Build production-grade systems
Deploy production-grade systems
Integrate data pipelines
Integrate cloud infrastructure
How You'll Work.
Team & Collaboration
Work closely with ML researchers; Work closely with platform engineers; Work closely with scientists; Work with ML researchers; Work with engineers; Work with scientists; Work cross-functionally with scientists; Work cross-functionally with data engineers; Work cross-functionally with product managers
Communication Scope
explain complex ideas to diverse audiences
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