Senior Machine Learning Engineer

G MASS
Charing Cross, United Kingdom
4 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
£ 63K

Job location

Charing Cross, United Kingdom

Tech stack

Amazon Web Services (AWS)
Cloud Computing
Continuous Integration
Data Warehousing
DevOps
Python
Machine Learning
SQL Databases
Snowflake
GIT
Scikit Learn
Kubernetes
Information Technology
Docker

Job description

  • 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 & conditions

Salary: to be discussed, depending on experience

Length: 6 months, with the view to extend

About the company

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.

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