Senior Machine Learning Engineer

Gmassconsulting; Greater London; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading Audit and Advisory firm in Greater London seeks a Machine Learning Engineer to develop and scale their pricing technology. This role includes building ML platforms and collaboration across teams to ensure effective model deployment. Candidates should have a degree in Data Science or similar, along with strong ML lifecycle management experience and proficiency in Python. A competitive salary will be discussed based on experience, along with an initial 12-month contract with the potential to extend.

Benefits

Salary to be discussed, depending on experience

12-month contract with view to extend

Qualifications

• 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)

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

Skills

Machine Learning model lifecycle management

Statistical methods

Python programming

DevOps practices

Collaborative communication

Education

Bachelor's or Master's degree in Statistics, Data Science, or Computer Science

Tools

Kubernetes

Docker

AWS

Snowflake

Git

Job description

Job Overview

G MASS Consulting are supporting a leading Audit and Advisory business. We'reumeric 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 MLUBL 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