Lila Sciences

StaffEngineer,DataPlatform

$215–300k ~AI est. Cambridge, Massachusetts, United States
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff Engineer, Data Platform at Lila Sciences. Skills: Data platform architecture, Data infrastructure, MLOps, Cloud infrastructure. Design data infrastructure. Evolve data infrastructure”

Industry & Context.

Problems you'll solve

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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