Senior Machine Learning Engineer

Tate; City of Westminster; Hybrid; GBP 80,000 - 95,000; Full time

Job summary

A leading digital gaming company in London is looking for a Senior Machine Learning Engineer to design and implement production-grade ML systems. This hybrid role focuses on optimizing algorithms and building scalable solutions to enhance customer engagement. Candidates should have a Master's degree in a quantitative field and over 3 years of experience in ML engineering. Familiarity with AWS, Python, and containerization is essential. Competitive salary of up to £95,000 based on experience.

Qualifications

• 3+ years of industrial ML engineering experience, not purely academic.
• Production-grade Python proficiency and ability to write clean, maintainable code.
• Hands-on experience with AWS (ideally AWS-certified).

Responsibilities

• Develop, validate, and optimise predictive models using advanced ML algorithms.
• Deploy models as APIs, batch jobs, and streaming services.
• Partner with Data Scientists and business stakeholders to translate insights into production-ready solutions.

Skills

Machine Learning

Python

SQL

AWS

Docker

Kubernetes

Data Science Fundamentals

Education

Masters degree in a STEM or quantitative discipline

Tools

AWS Lambda

AWS CloudWatch

CI/CD

Job description

Job Overview

We are seeking a Senior Machine Learning Engineer to design and deliver production‑grade ML systems for a leading digital gaming and gambling platform based in London (Hybrid – 2 days onsite). This hands‑on role combines data science expertise with engineering skills, where you will build models, optimise algorithms, and deploy solutions at scale to enhance customer engagement and decisioning. If you are passionate about applied AI, data‑driven problem solving, and building ML systems that deliver measurable impact, this is the role for you. The salary for this position is up to £95,000 depending on experience.

Responsibilities

• Develop, validate, and optimise predictive models using advanced ML algorithms (e.g., gradient boosting, logistic regression, ensemble methods)
• Deploy models as APIs, batch jobs, and streaming services; implement CI/CD, monitoring, and rollback strategies
• Build scalable data workflows and feature stores for ML applications
• Containerise applications with Docker, orchestrate with Kubernetes, and deploy securely in AWS
• Apply best practices for evaluation, drift monitoring, and compliance
• Partner with Data Scientists and business stakeholders to translate insights into production‑ready solutions

Technologies

• AI
• AWS
• Lambda
• CI/CD
• CloudWatch
• Docker
• IAM
• Kubernetes
• Machine Learning
• Python
• SQL
• Cloud

Qualifications

• Masters degree in a STEM or quantitative discipline (PhD nice to have)
• 3+ years of industrial ML engineering experience (not purely academic; not focused on Generative AI)
• Strong data science fundamentals: supervised learning, evaluation metrics, feature engineering, and experimentation
• Production‑grade Python proficiency and ability to write clean, maintainable code
• Comfortable with complex SQL queries
• Hands‑on experience with AWS (ECR/ECS/EKS, Lambda, S3, IAM, CloudWatch), ideally AWS‑certified
• Experience with Docker and Kubernetes in production environments
• Strong communication skills and ability to explain technical concepts clearly