Senior Software Engineer, Scientific System of Record

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

Offered From the posting source checked Jun 20, 2026

Verification

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Salary

$144K-$240K From the posting source checked Jun 20, 2026

401(k) match

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

65% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Senior From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Company

Company stage

Early From the posting source checked Jun 20, 2026

Equity

Offered From the posting source checked Jun 20, 2026

Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Senior Software Engineer, Scientific System of Record Cambridge, MA USA; San Francisco, CA USA Your Impact at LILA Join us in shaping the future of science! We are seeking Senior Software Engineers with full stack experience to join our Scientific System of Record Team (SSR), where you'll collaborate with software engineers, lab scientists, and machine learning engineers to build cutting-edge tools for automated scientific analysis and more. If you thrive in a collaborative, fast-paced environment and bring best practices in git, development workflows, and user-centered design, we want to hear from you! About The Team The Scientific System of Record Team (SSR) builds the memory layer for Lila's operations. It answers two questions: what did we plan to build? and what actually happened? These systems connect scientific intent to physical reality. Together with the data and automation teams, their systems ensure reproducibility and close the Design-Build-Test-Learn (DBTL) loop. What You'll Be Building - Lab Execution and Scientific Workflows: Build systems that model scientific intent, experiment planning, protocol execution, sample and asset state, operational events, and results capture across complex lab workflows. - User Interfaces and APIs: Design and implement high-quality, secure, and well-documented UIs and APIs that support scientists, automation systems, ML workflows, and AI-driven applications. - Application Development: Build front-end and backend services with a focus on performance, maintainability, and reliability. - Data and System Modeling: Develop domain models, schemas, indexes, and data contracts across SQL, NoSQL, vector databases, data lakehouses, and other scientific data systems. - Reliability, Performance,

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