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- Tasks: Design and deliver production-grade ML systems for a leading gaming platform.
- Company: Join a dynamic digital gaming and gambling company in London.
- Benefits: Competitive salary up to £95,000, hybrid work, and career growth opportunities.
- Why this job: Make a real impact with applied AI and data-driven solutions.
- Qualifications: Master's degree in STEM, 3+ years of ML engineering experience, and strong Python skills.
- Other info: Collaborative environment with a focus on innovation and inclusivity.
The predicted salary is between 72000 - 108000 £ per year.
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.
- 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 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.
Senior Machine Learning Engineer in London employer: Tate
Contact Detail:
Tate Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Machine Learning Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with other Machine Learning Engineers on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your ML projects, especially those involving Python, SQL, and AWS. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for technical interviews by brushing up on your data science fundamentals and coding skills. Practice common ML problems and be ready to explain your thought process clearly—communication is key!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to make an impact in the world of ML.
We think you need these skills to ace Senior Machine Learning Engineer in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the Senior Machine Learning Engineer role. Highlight your experience with Python, SQL, AWS, Docker, and Kubernetes, as these are key skills we're looking for. A personalised CV shows us you’re genuinely interested in the position!
Craft a Compelling Cover Note: In your cover note, give us a brief overview of your relevant experience and why you're excited about this role. This is your chance to showcase your passion for applied AI and data-driven problem solving, so make it count!
Showcase Your Projects: If you've worked on any interesting ML projects, don’t forget to mention them! We love seeing real-world applications of your skills, especially those that demonstrate your ability to build production-grade systems.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it makes the whole process smoother for everyone involved!
How to prepare for a job interview at Tate
✨Know Your ML Algorithms
Brush up on your knowledge of advanced machine learning algorithms like gradient boosting and ensemble methods. Be ready to discuss how you've applied these in past projects, as this will show your hands-on experience and understanding of the concepts.
✨Showcase Your Engineering Skills
Prepare to talk about your experience with deploying models as APIs and using CI/CD practices. Highlight any specific projects where you containerised applications with Docker or orchestrated them with Kubernetes, as this is crucial for the role.
✨Demonstrate Collaboration
Think of examples where you've worked closely with Data Scientists or business stakeholders. Be ready to explain how you translated insights into production-ready solutions, showcasing your ability to communicate technical concepts clearly.
✨Prepare for Technical Questions
Expect questions on SQL queries and AWS services. Brush up on your knowledge of AWS tools like Lambda and S3, and be prepared to discuss how you've used them in your previous roles. This will demonstrate your technical proficiency and readiness for the job.
