Lila Sciences
StaffEngineer,DataPlatform
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Engineer, Data Platform at Lila Sciences. Skills: Data platform architecture, Data infrastructure, MLOps, Cloud infrastructure. Design data infrastructure. Evolve data infrastructure”
Industry & Context.
Translate domain requirements
What They're Looking For.
Must Have
Bachelor's or Master's degree, 8+ years software or data engineer, Fluent in Python and SQL, Production experience relational/NoSQL databases, Experience with cloud infrastructure, Experience with containerized deployment
Nice to Have
Experience with workflow orchestration systems, Experience building data infrastructure for agentic/LLM workflows, Background in scientific computing, Background in life sciences, Background in research software, Proficiency with AI-assisted development tools
What You'll Do.
Design data infrastructure
Evolve data infrastructure
Make build-vs-buy decisions
Establish architectural patterns
Build reliable pipelines
Operate orchestration systems
Extend orchestration systems
Ensure fault tolerance
Ensure reproducibility
Define schema evolution
Maintain schema evolution
Define data contracts
Maintain data contracts
Partner with researchers
Partner with scientists
Partner with engineers
Translate requirements
Establish coding standards
Establish review standards
Establish design standards
How You'll Work.
Team & Collaboration
Cross-functional teams; ML researchers; Lab scientists; Product engineers
Communication Scope
Explain technical trade-offs
Full Job Description
Your Impact at LILA Lila Sciences is building the software platform that makes automated scientific discovery possible. At the heart of that platform is data: raw outputs from laboratory instruments, experimental model results, curated public datasets, and the scientific literature that contextualizes all of it. The data platform team is responsible for the infrastructure that moves, stores, transforms, and surfaces this data across the organization. We are looking for a Staff Engineer to set the technical direction for our core data infrastructure: ingestion frameworks, storage architecture, orchestration patterns, and the interfaces that let scientists and ML researchers work with data reliably at scale. You will work closely with software engineers, machine learning researchers, and lab scientists to understand requirements and translate them into durable platform capabilities. This is a role for engineers who care deeply about how data systems are designed. You will establish the architectural patterns and engineering standards the broader team builds on, mentor engineers across the data platform group, and make technical decisions that compound over time. What You'll Be Building Data Platform Architecture: Design and evolve the core data infrastructure that ingests, stores, and serves data across scientific and ML workflows. Make principled build-vs-buy decisions and establish architectural patterns adopted by the broader engineering organization. Ingestion and Integration: Build reliable pipelines that bring in data from diverse sources: laboratory instruments, public scientific datasets, and external research literature. Own the interfaces between upstream producers and downstream consumers. Orchestration and Reliability: Operate and extend workflow orchestration systems that run complex, multi-step scientific pipelines. Ensure observability, fault tolerance, and reproducibility across the data stack. Data Modeling and Schema Strategy: Define and maintain dat
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