---
title: 'Staff Engineer, Data Platform at Lila Sciences'
canonical: 'https://feeny.ai/job/staff-engineer-data-platform-lila-sciences-cambridge-3k9mbh4ejc7h'
type: 'job'
last_seen: '2026-09-04'
---

# Staff Engineer, Data Platform at Lila Sciences

- **Company:** Lila Sciences
- **Location:** Cambridge, MA / San Francisco, CA
- **Compensation:** $192k–$272k
- **Posted:** 2026-06-02
- **Last confirmed live:** 2026-09-04
- **Apply:** https://job-boards.greenhouse.io/lilasciences/jobs/4222065009

## 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 data models, schema evolution practices, and data contracts that ensure consistency, discoverability, and long-term durability of scientific and platform data assets.
- Cross-Functional Technical Leadership: Partner with ML researchers, lab scientists, and product engineers to translate scientific and research requirements into platform capabilities. Drive alignment on data standards and integration patterns across teams.
- Engineering Standards and Mentorship: Establish coding, review, and design standards for the data platform team. Mentor engineers, lead design reviews, and raise the technical bar across the group.

## What You’ll Need to Succeed

- Bachelor's or Master's degree in Computer Science, Engineering, or a related field, and 8+ years as a software or data engineer with a focus on building and operating data infrastructure.
- Designed and shipped data platform components from the ground up, including ingestion frameworks, storage abstractions, and orchestration systems. Fluent in Python and SQL and writes production-quality code.
- Production experience with relational and NoSQL databases, schema design, query optimization, and operational concerns at scale. Comfortable working across structured, semi-structured, and unstructured data.
- Proven track record of working cross-functionally with scientists, ML researchers, and engineers. Able to translate domain requirements into platform decisions and explain technical trade-offs to diverse audiences.
- Experience with cloud infrastructure and containerized deployment (AWS, Kubernetes).
- Hands-on experience with modern table formats and open lakehouse patterns (Iceberg, Delta Lake, Hudi).

Bonus Points For

- Experience with workflow orchestration systems (Flyte, Airflow, Dagster, or similar).
- Experience building data infrastructure that serves agentic and LLM-driven workflows, including vector databases, RAG infrastructure, and retrieval-optimized data access patterns.
- Background in scientific computing, life sciences, or research software.
- Proficiency with AI-assisted development tools (Cursor, Claude Code, or similar) and ability to incorporate them effectively into day-to-day engineering work.

## Compensation

We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.

U.S. Benefits. Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office based employees; and a company subsidized lunch program.

International Benefits. Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.

Expected Base Salary Range $192,000—$272,000 USD

## About LILA

Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves.

LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Learn more at www.lila.ai.

Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.

We’re All In

Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.

Information you provide during your application process will be handled in accordance with our [Candidate Privacy Policy](https://www.lila.ai/candidate-privacy-policy-notice).

A Note to Agencies

Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.

## About Lila Sciences

## Company Overview
- **One-liner**: Lila Sciences is building the world’s first Scientific Superintelligence platform and autonomous lab, using AI to autonomously generate hypotheses, design and run experiments, and learn from results in real time across life sciences, chemistry, materials, energy, and defense.
- **Entity Type**: Private (Privately Held) – Series A, Seed, and Grant funding rounds
- **Headquarters**: Cambridge, Massachusetts, United States
- **Founded**: Not publicly available (first funding round was Seed in March 2025)
- **Founders**: Not publicly available (founded within Flagship Pioneering’s ecosystem)

## Core Business
- **Primary industry**: AI-powered scientific discovery and autonomous laboratory platforms
- **Target customers**: B2B – research organizations, biotech, pharmaceutical, energy, materials, aerospace, and defense companies
- **Mission**: “Scientific Superintelligence to solve humankind’s greatest challenges” – accelerating discovery across medicine, materials, energy, and defense

## Products & Services
- **LILA Platform (Scientific Superintelligence)**: An AI model and operating system that autonomously executes the entire scientific method – generating hypotheses, designing experiments, running them in physical labs, and learning from results in real time.
- **AI Science Factory™ Instruments**: Proprietary hardware and robotics that serve as the “body” of the platform, enabling automated experimentation at scale.
- **Domain-specific applications**: Tailored solutions for biotech (drug discovery, protein engineering), therapeutics (mRNA, antibodies, cell therapies), energy & environment (clean fuels, catalysis, critical minerals), advanced materials, chemicals, aerospace & defense, and oil & gas.

## Market Standing
- **Valuation**: Not disclosed
- **Key Metric**: Total funding – USD $550.7M (as of LinkedIn data)
  - Seed Round (March 2025): $200M led by Flagship Pioneering
  - Series A (September 2025): $235M led by Braidwell and Collective Global Management
  - Series A (November 2025): $115M led by NVentures (NVIDIA)
  - Grant (January 2026): $671,400 led by ARIA
- **Notable Investors/Partners**: Flagship Pioneering, NVIDIA (NVentures), Braidwell, Collective Global Management, ARIA
- **Growth Signals**: Named #25 on the 2026 CNBC Disruptor 50 List; headcount of 308 employees (monthly growth +10.6%); 122 active job postings; operates in 6 countries (US, UK, Canada, Poland, Spain, Germany)

## Competitive Advantages
- **Proprietary AI model** that consistently outperforms other models across scientific domains in complex analysis and reasoning.
- **Autonomous physical labs** that close the loop between AI hypothesis generation and real-world experimentation.
- **“Team of Teams” operating model** enabling startup speed at scale while maintaining radical transparency and high trust.
- **General platform approach** (inspired by Rich Sutton’s “Bitter Lesson”) rather than narrow domain-specific tools, allowing broad applicability.

## Strategic Focus
- Accelerating discovery across medicine, materials, energy, and defense
- Scaling the autonomous science platform to more industries and use cases
- Building “Scientific Superintelligence” that can tackle humanity’s greatest challenges
- Continued investment in AI research, robotics, and lab automation

## Why Work Here
- **Culture**: Emphasizes velocity, trust, curiosity, truth, and grit. “Think freely, prove precisely.” A high-trust, mission-driven environment where scientists and engineers work side by side.
- **Remote/Hybrid/Office**: Roles are listed in Cambridge, MA; San Francisco, CA; and London, UK. Physical lab presence suggests significant on-site work, but some roles may offer flexibility. Policy not explicitly stated.
- **Notable perks/engineering culture**: Opportunity to work at the frontier of AI and scientific discovery; collaboration with world-renowned experts; access to cutting-edge robotics and AI infrastructure; strong emphasis on learning and teaching (“generous teachers and eager learners”).

## Sources
1. [lila.ai](https://www.lila.ai/)
2. [lila.ai/about](https://www.lila.ai/about)
3. [lila.ai/open-roles](https://www.lila.ai/open-roles)
4. [LinkedIn - Lila Sciences](https://www.linkedin.com/company/lila-sciences)
5. [Greenhouse Job Board](https://job-boards.greenhouse.io/lilasciences/jobs/4246302009)

## Other roles at Lila Sciences

- [Data Scientist II / Senior Data Scientist, Life Sciences](https://feeny.ai/job/data-scientist-ii-senior-data-scientist-life-sciences-lila-sciences-cambridge-wvrt5y3pkr50) — Cambridge, MA
- [Senior Data Engineer, Bioinformatics, Cheminformatics, Materials](https://feeny.ai/job/senior-data-engineer-bioinformatics-cheminformatics-materials-lila-sciences-san-kp5d4nbn38vz) — San Francisco, CA
- [Associate Director, App](https://feeny.ai/job/associate-director-app-lila-sciences-cambridge-46qgd5hp866e) — Cambridge, MA / San Francisco, CA
- [Maintenance Engineering Technician II](https://feeny.ai/job/maintenance-engineering-technician-ii-lila-sciences-cambridge-qgp4st6zk9gw) — Cambridge, MA
- [Research Scientist, Photonic Materials Discovery](https://feeny.ai/job/research-scientist-photonic-materials-discovery-lila-sciences-cambridge-m87b6zgatgmg) — Cambridge, MA
- [Research Scientist I/II, Computational Organic Electronics](https://feeny.ai/job/research-scientist-i-ii-computational-organic-electronics-lila-sciences-mh2tq43ahp5d) — Cambridge, MA
- [Associate Engineer/ Engineer I, Formulations and Characterization](https://feeny.ai/job/associate-engineer-engineer-i-formulations-and-characterization-lila-sciences-6dy4t3wbbqar) — Cambridge, MA
- [Senior Manager, Scientific Discovery Capacity Planning](https://feeny.ai/job/senior-manager-scientific-discovery-capacity-planning-lila-sciences-cambridge-c1tjq0yzrj9f) — Cambridge, MA
- [Finance Business Partner, AI & Software](https://feeny.ai/job/finance-business-partner-ai-software-lila-sciences-cambridge-dme1cxf7yazg) — Cambridge, MA
- [Associate Director / Director, Strategic Finance](https://feeny.ai/job/associate-director-director-strategic-finance-lila-sciences-cambridge-fp5gxvaqvt2k) — Cambridge, MA