Senior Machine Learning Engineer

Tate; City Of London; Hybrid; GBP 80,000 - 95,000; Full time

Job summary

A leading digital gaming platform seeks a Senior Machine Learning Engineer to design and deliver production-grade ML systems. This hybrid role requires expertise in model development, data science, and cloud deployment. Candidates should have over three years of experience in ML engineering, strong Python and SQL skills, and a Master's degree in a STEM field. The position involves collaboration with data scientists and stakeholders to ensure robust and scalable solutions.

Qualifications

• 3+ years of industrial ML engineering experience, not purely academic.
• Strong data science fundamentals including supervised learning and feature engineering.
• Hands-on experience deploying applications in cloud environments.

Responsibilities

• Develop, validate, and optimize predictive models using advanced ML algorithms.
• Deploy models as APIs and implement CI/CD strategies.
• Build scalable data workflows and feature stores for ML applications.

Skills

Machine Learning algorithms

Python proficiency

SQL queries

AWS services

Docker

Kubernetes

Communication skills

Education

Master's degree in a STEM discipline

PhD in a quantitative discipline (desirable)

Tools

AWS (ECR/ECS/EKS, Lambda, S3, IAM, CloudWatch)

Docker

Kubernetes

Job description

Senior Machine Learning Engineer - Data Science Focus

Based in London (Hybrid - 2 days onsite)

Permanent, Full-Time

Salary: Up to 95,000 (depending on experience)

We are seeking a Senior Machine Learning Engineer to design and deliver production-grade ML systems for a leading digital gaming and gambling platform. This is a hands‑on role combining data science expertise with engineering skills - you'll build models, optimise algorithms, and deploy solutions at scale to enhance customer engagement and decisioning.

You’ll work closely with Data Scientists to translate prototypes into robust applications, ensuring performance, governance, and reliability. If you're passionate about applied AI, data-driven problem solving, and building ML systems that deliver measurable impact, this is the role for you.

Role and Responsibilities

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

Key Skills and Experience

• Master's 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.
• Degree (BSc/MSc) in a STEM or quantitative discipline; PhD desirable.
• Strong communication skills and ability to explain technical concepts clearly.

Apply now with your most up-to-date CV and a short note highlighting your experience with Python, SQL, AWS, Docker, Kubernetes, and data science projects.

Please be aware this advert will remain open until the vacancy has been filled. Interviews will take place throughout this period, therefore we encourage you to apply early to avoid disappointment.

Tate is acting as an Employment Business in relation to this vacancy.

Tate is committed to promoting equal opportunities. To ensure that every candidate has the best experience with us, we encourage you to let us know if there are any adjustments we can make during the application or interview process. Your comfort and accessibility are our priority, and we are here to support you every step of the way. Additionally, we value and respect your individuality, and we invite you to share your preferred pronouns in your application.