Help build machine learning software and infrastructure that supports sustainability science from research through production.

Design and build reusable data and ML infrastructure, including libraries, configuration-driven interfaces, and infrastructure-as-code components for data processing, model training, and inference.
Create tooling for repeatable experiments and model comparisons, preserving the data, code, and configuration required to investigate results.
Develop and evaluate AI-assisted engineering workflows, enabling coding agents to use the platform correctly.
Implement automated checks and appropriate review to assess coding agent outputs.
Measure whether AI-assisted workflows improve engineering productivity while maintaining reliability.
Support adoption and ongoing evolution by partnering with platform users to identify recurring needs, document design trade-offs, and maintain compatibility as shared components change.

5+ years of non-internship professional software development experience.
5+ years of programming with experience in at least one software programming language.
5+ years leading design or architecture work, including design patterns, reliability, and scaling of new and existing systems.
Experience as a mentor, tech lead, or leading an engineering team.
5+ years across the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
Bachelor's degree in computer science or equivalent.

Health insurance (medical, dental, vision, prescription, Basic Life & AD&D, with option for Supplemental life plans)
EAP
Mental Health Support
Medical Advice Line
Flexible Spending Accounts
Adoption and Surrogacy Reimbursement coverage
401(k) matching
Paid time off
Parental leave
Sign-on payments
Restricted stock units (RSUs)

Applied scientists and engineers build models and software for sustainability applications.
Work spans research and production, creating both scientific methods and the systems to use them reliably.
Reusable tools help ensure new research projects do not require building infrastructure from scratch each time.

Senior Machine Learning Engineer, Sustainability Science and Innovation

Job Description