Policy Expert is hiring a Lead Machine Learning Engineer to build the ML platform that powers the next wave of AI-driven products. You will design and ship scalable, reusable infrastructure in GCP to enable Data Scientists to experiment quickly and deploy models confidently. This is a hands-on leadership role, mentoring a team while bridging the gap between experimentation and reliable production systems.
What You'll Do
- Design, implement and standardise end-to-end machine learning pipelines using Vertex AI Pipelines, Model Registry, and Cloud Run.
- Build reusable components and templates to accelerate model delivery across squads.
- Develop MLOps frameworks and SDKs around metadata tracking, feature versioning, model governance, and CI/CD integration.
- Optimise data processing and orchestration using BigQuery, Cloud Composer and Pub/Sub.
- Act as a bridge between Data Science, Product, and Platform teams to ensure smooth delivery of ML solutions.
- Review architecture, design decisions, and code to maintain high engineering standards.
- Foster a culture of engineering excellence, collaboration, and continuous learning within the team.
- Stay close to emerging trends in ML systems, generative AI, and agents; evaluating their fit within the MLOps landscape.
What We're Looking For
- A degree in Computer Science, Software Engineering, Data Science or another quantitative field.
- 6+ years of experience in building and deploying ML systems.
- Able to balance being a hands-on Engineer while also leading or mentoring a team of Engineers.
- Strong communicator who can work effectively with Data Scientists, Product Managers and Engineering teams.
- Highly proficient in Python: writing clean, testable, modular code suitable for CI/CD environments.
- A track record of designing MLOps or ML platform tooling, not just consuming it.
- Strong understanding of model lifecycle automation, including reproducibility, validation, drift detection and rollback strategies.
- Solid grasp of containerisation and infrastructure-as-code (Docker, GCP, IAM).
- A collaborative, pragmatic mindset and very comfortable discussing architecture with Engineers, Data Scientists and non-technical stakeholders.
Nice to Have
- Familiar with neural network frameworks such as PyTorch with an interest in GenAI or agentic workflows (LangChain, Vertex AI Agents, etc…).
- Knowledge of the insurance industry.
Technical Stack
- Languages & Frameworks: Python, PyTorch, LangChain
- GCP & MLOps: Vertex AI Pipelines, Model Registry, Cloud Run, BigQuery, Cloud Composer, Pub/Sub
- Infrastructure & Tools: Docker, Terraform, GitHub Actions
Team & Environment
Lead and mentor a team of Machine Learning Engineers. Work closely with Data Science and Product teams.
Benefits & Compensation
- Pension contributions matched up to 7%.
- Private medical & Dental cover.
- Learning budget of £1,000 a year + Study leave.
- Enhanced maternity & paternity.
- Travel season ticket loan.
- Access to a wide selection of London O2 events and use of a Private Lounge.
- Employee Wellbeing Programme.
- Prayer room in Office.
Work Mode
This role is hybrid, based in London.
We pride ourselves on being an equal opportunity employer. We treat all applications equally and recruit based solely on an individual’s skills, knowledge, and experience.
