Senior MLOps Engineer

ClimateAi is an ESG and sustainability consultancy registered in England and Wales that helps organisations navigate the full spectrum of sustainability challenges, from green building certifications and ESG reporting to digital product passports and regulatory compliance. The company delivers data-driven, AI-enabled solutions designed to support businesses operating across multiple sectors, jurisdictions, and evolving regulatory environments, with a focus on making sustainability outcomes measurable, transparent, and audit-ready. Their services span strategy development, risk management, asset tracking, and supply chain transparency, serving clients in the built environment, manufacturing, consumer products, and supply chain sectors internationally. ClimateAi positions itself as an end-to-end sustainability partner, supporting organisations from initial strategy through to practical implementation and ongoing compliance. With a team of certified assessors and over 40 sustainability projects delivered, the consultancy emphasises long-term ESG resilience and helping clients turn environmental responsibility into a competitive business advantage.

The Role

As a Senior MLOps Engineer, you will own the infrastructure and ML platform that powers ClimateAi’s forecasting and risk products. You will design, build, and operate the cloud systems, data management infrastructure, and model lifecycle tooling that allow our Data Science and ML Engineering teams to develop, compare, register, and ship models with confidence.

This is a high-leverage role at the intersection of infrastructure, ML platform, and security. You will partner closely with Data Science to unblock initiatives like SYO2 and Risk Outlooks model improvements by giving them a real model management platform; with Data Engineering to harden our data lakehouse and pipelines; and with our security lead to provide a strong second engineer on cloud security — building skill duplication across critical systems.

Our hybrid work schedule includes 3 in-person days at one of our core locations (SF,  Boston) and 2 remote days.

What You’ll Do

• Stand up and operate the ML model framework that provides ML engineers and data scientists experiment tracking, model registry, and lineage
• Own and evolve our Infrastructure as Code so environments are reproducible, auditable, and easy for engineers to extend
• Build CI/CD and deployment patterns for ML pipelines and models, including reproducible training, automated validation, and safe rollouts to production
• Improve data management systems alongside Data Engineering with storage tiering, lifecycle and retention, cost-performance tradeoffs, and observability across our cloud environments
• Author clear architectural documentation, runbooks, and design proposals to communicate tradeoffs to engineering and non-technical stakeholders

What We’re Looking For

• 3–5 years of experience in Machine Learning, Backend Software Engineering, Data Engineering, or MLOps roles supporting data-intensive systems in production
• Production experience with ML lifecycle management platforms such as MLFlow, Weights & Biases, Neptune.ai, Comet.ml or similar
• Experience with IaC using Terraform, Pulumi, OpenTofu, Encore, Crossplane or similar
• Deep experience with building systems-of-systems in AWS, GCP, or Azure, that span across multiple services or multiple cloud providers
• Strong communication and ownership. You scope your work, monitor what you ship, and drive problems to permanent resolution
• Ability to collaborate closely with Data Scientists, Engineers, and Product, to design and support end-to-end ML workflows.

Bonus Points

• Experience with training, inference, deploying, and scaling modern ML models to production
• Experience with configuring models with datasets up to the petabyte-scale

Leveling

This role is posted at our Senior Engineer (P3) level. You will be a self-directed engineer who independently designs, implements, and optimizes complex infrastructure and ML platform components, drives data and model quality, supports cross-functional teams, and provides technical mentorship within the team. Leveling decisions are made in partnership with candidates through the interview process.

Compensation

The base compensation range for employees based in the US is $170,000-200,000 and equity in line with experience and company stage. This salary range may be inclusive of several career levels at ClimateAi and will be narrowed during the interview process based on a number of factors, including the candidate’s experience, qualifications, business need and US location.

ClimateAi is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.