Senior ML Engineer
governr · London (Hybrid, 2-3 days/week)
Senior ML Engineer
5+ years experience · Machine learning · Data pipelines · MLOps · FastAPI
governr is the AI control infrastructure for regulated industries. We help organisations govern AI safely, compliantly, and at scale. We're looking for a Senior ML Engineer who can bridge the gap between research and production. Someone who's as comfortable designing data pipelines as they are deploying models that hold up in regulated environments.
You'll work at the intersection of data engineering, machine learning, and AI agent development. If you're energised by technically hard problems with real-world consequences, this is the role for you.
What you'll do
- Design and build robust ETL/ELT data pipelines, including scheduling and orchestration using Airflow, Prefect or similar
- Work across the full ML lifecycle: data preparation, model training, evaluation, deployment and monitoring
- Build and maintain RESTful services and APIs using FastAPI to serve models and integrate with the broader platform
- Develop and integrate AI agents into our platform, including LLM integration, tool use and orchestration
- Work with data-centric Python libraries including Pandas and NumPy, with PySpark or similar a strong plus
- Collaborate closely with analysts, engineers and non-technical stakeholders to translate requirements into reliable, scalable solutions
- Contribute to technical architecture decisions and help set standards for ML engineering across the team
What we're looking for
- 5+ years of experience in machine learning engineering, data engineering or a closely related role
- Strong core Python skills: data structures, OOP, packaging and testing
- Hands-on experience building and maintaining data pipelines in production
- Practical exposure to ML workflows: model training, evaluation and deployment, even if you're not a pure data scientist
- Experience with FastAPI in production environments
- Solid understanding of software design principles, testing and security best practices
- Excellent communication skills, able to work with both technical and non-technical stakeholders
- Financial services or regulated industry experience is a bonus
- Comfortable using AI tools to support and accelerate your work. We actively encourage it
Nice to have
- Experience with MLOps tooling such as MLflow, SageMaker, Vertex AI, Kubeflow or feature stores
- Familiarity with experimentation frameworks and measurement of model and business impact (KPIs, A/B testing)
Why governr
You'll be working on genuinely interesting problems with a team that cares about engineering quality. You'll have direct access to the founders and real input into how we architect and grow the platform. Competitive salary and benefits. Hybrid working, 2 to 3 days a week in our London office.
AI infrastructure for regulated industries is one of the most technically demanding spaces right now. You'll be building at the sharp end of it.