Design and own machine learning platforms for pricing technology, streamline workflows, and ensure reliable model performance at scale.
G MASS Consulting are supporting a leading Audit and Advisory business. We’re looking for a Machine Learning Engineer to shape and scale their pricing technology. In this role, you’ll design and own ML platforms that streamline pricing workflows, support rapid model deployment, and ensure models perform reliably at scale. Partnering with Data Science, Actuarial, and Product teams.
Responsibilities:
- Build and support ML lifecycle tooling for model deployment, monitoring, and alerting
- Maintain and improve the Kubeflow environment for Data Scientists and Actuaries
- Create pricing analytics tools to accelerate impact analysis and reduce manual work
- Collaborate with pricing and product teams to deliver high-impact tooling
- Communicate complex concepts clearly to technical and non-technical audiences
Requirements
- Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science, or a related field
- Strong experience managing the full ML model lifecycle (batch and online)
- Solid understanding of statistical methods, including GLMs and modern ML techniques
- Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn)
- Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows
- Familiarity with cloud platforms (AWS) and cloud data warehouses (Snowflake/SQL)
Benefits
Salary: to be discussed, depending on experience
Length: 12 months, with the view to extend
Similar Jobs
Artificial Intelligence • Semiconductor
Develop and optimise large-scale ML models for Graphcore hardware, scale training/inference across thousands of accelerators, benchmark and debug performance, run experiments, collaborate with Research and Software teams, and contribute code reviews and community engagement.
Top Skills:
C++JaxPythonPyTorch
Artificial Intelligence • Semiconductor
Develop, implement and optimise large-scale ML models for Graphcore hardware; benchmark and scale training/inference across thousands of accelerators; test internal releases, fix and review code; design and run experiments; collaborate with Research, Software and Product teams; engage with the AI community.
Top Skills:
C++JaxPythonPyTorch
Artificial Intelligence • Semiconductor
Develop, optimize, benchmark and scale state-of-the-art ML models for Graphcore hardware; run large-scale distributed training (64+ accelerators); test internal software releases, identify performance bottlenecks, design and execute ML experiments, collaborate with Research, Software and Product teams, and engage with the AI community.
Top Skills:
C++JaxPythonPyTorch
What you need to know about the London Tech Scene
London isn't just a hub for established businesses; it's also a nursery for innovation. Boasting one of the most recognized fintech ecosystems in Europe, attracting billions in investments each year, London's success has made it a go-to destination for startups looking to make their mark. Top U.K. companies like Hoptin, Moneybox and Marshmallow have already made the city their base — yet fintech is just the beginning. From healthtech to renewable energy to cybersecurity and beyond, the city's startups are breaking new ground across a range of industries.
