G MASS Consulting

Senior Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Machine Learning Engineer with a 6-month contract, focusing on ML lifecycle tooling and pricing technology. Key skills include Python, Kubernetes, AWS, and statistical methods. A relevant degree and extensive ML experience are required.
🌎 - Country
United Kingdom
💱 - Currency
£ GBP
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💰 - Day rate
Unknown
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🗓️ - Date
January 7, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Unknown
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📄 - Contract
Fixed Term
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🔒 - Security
Unknown
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📍 - Location detailed
London, England, United Kingdom
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🧠 - Skills detailed
#Cloud #Pandas #Snowflake #Computer Science #Data Science #Python #Kubernetes #Monitoring #SQL (Structured Query Language) #AWS (Amazon Web Services) #ML (Machine Learning) #Docker #Statistics #Batch #GIT #DevOps #Consulting #Model Deployment #Deployment #Data Warehouse
Role 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 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: 6 months, with the view to extend