Senior Machine Learning Engineer

G MASS; Greater London; On-site; GBP 70,000 - 110,000; Full time

Job summary

G MASS Consulting is seeking a Machine Learning Engineer in London to design and own ML platforms for pricing workflows, enabling rapid model deployment and scalable performance. You will partner with Data Science, Actuarial, and Product teams to deliver impactful tooling.

Responsibilities include building deployment and monitoring tooling, maintaining Kubeflow environments, and delivering production-grade Python applications while communicating effectively with technical and non-technical

Qualifications

• Bachelor's or Master's in Statistics, Data Science, CS or related field.
• Experience managing full ML lifecycle (batch and online).
• Strong Python (pandas, scikit-learn) experience.

Responsibilities

• Build and support ML lifecycle tooling for model deployment, monitoring, and alerting
• Maintain and improve 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

Skills

ML lifecycle

Python programming

Data analysis

Communication

DevOps culture

Education

Bachelor's or Master's in Statistics/Data Science/CS

Tools

Kubeflow

Docker

CI/CD

Git workflows

Kubernetes

Snowflake

Job description

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

• 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)

Salary: to be discussed, depending on experience

Length: 12 months, with the view to extend