ML Tech Lead

Sky; Tottenham; On-site; GBP 80,000 - 100,000; Full time

Job summary

A leading technology company is looking for a Lead Machine Learning Engineer to advance their personalized recommendation systems. Responsibilities include developing efficient solutions that serve millions of users, collaborating across teams, and deploying machine learning models in production. The ideal candidate should have expertise in the machine learning lifecycle, advanced Python skills, and experience with recommendation systems and mentoring less experienced colleagues. The position offers competitive benefits and a supportive work environment.

Benefits

Private healthcare

Generous pension package

Discounted mobile and broadband

Sky VIP rewards

Qualifications

• Expertise in designing and deploying machine learning models.
• Experience with data pipeline engineering.
• Advanced proficiency in Python and ML libraries.

Responsibilities

• Develop and optimize machine learning models for user personalization.
• Construct scalable data pipelines for feature engineering.
• Monitor and maintain deployed ML models.

Skills

Machine learning lifecycle

Python

TensorFlow

PyTorch

A/B testing

Recommendation systems

Generative AI

Mentoring

Tools

TFX

Kubeflow

TensorFlow Serving

Triton

TorchServe

Job description

Job Overview

ID: 1855151

Date Posted: Posted 1 day ago

Expiration Date: 02/02/2026

Location: Competitive

What you'll do

We are seeking a highly skilled Lead Machine Learning Engineer to advance our personalised recommendation systems by developing efficient, low‑latency solutions that serve millions of users globally. The successful candidate will collaborate closely with data scientists, engineers, and product managers to design intelligent content recommendation mechanisms and drive the ongoing advancement of our Machine Learning Platform.

Responsibilities

• Model Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis.
• Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising large‑scale structured and unstructured datasets.
• Production Deployment: Deploy and supervise ML models in production environments, ensuring high availability, optimal performance, and continued relevance.
• Experimentation: Lead the design and analysis of A/B tests and offline experiments to evaluate model efficacy and support continuous improvement.
• Cross‑Functional Collaboration: Engage with multidisciplinary teams to align machine learning initiatives with business objectives and user needs.
• Research & Innovation: Evaluate emerging research in machine learning, deep learning, and personalisation for potential integration within existing systems.

What you'll bring

• Demonstrated expertise in the full lifecycle of machine learning, from model development, deployment and serving to monitoring and maintenance.
• Advanced proficiency in Python and knowledge of ML libraries/frameworks (e.g., TensorFlow, PyTorch).
• Experience using ML training frameworks (e.g., TFX, Kubeflow Pipelines SDK) and model serving technologies (e.g., TensorFlow Serving, Triton, TorchServe).
• Experience with high‑volume data processing and real‑time streaming architectures.
• Strong understanding of recommendation system design and personalisation algorithms.
• Familiarity with Generative AI and its applications in production settings.
• Exceptional communication and analytical problem‑solving skills.
• Proven successful experience in mentoring less experienced engineers to improve their technical skills.

A Typical Day at the Office

When you come in, you can grab a coffee or a bit of breakfast from one of the many subsidised cafés or restaurants on site. Settle in at your desk, have a quick look at Slack to see what's happening in the tech communities, then catch up with everyone at the team stand‑up. After that, you'll join your team and pick the first task to get cracking on. At lunchtime you'll have a few choices such as heading to The Pavilion for a bite with the team, popping to the onsite gym for a quick workout, or joining a lunchtime community meetup. Near the end of the day the team might have a quick coffee break before wrapping up with a team retrospective.

Benefits

• Sky Q, for the TV you love all in one place
• The magic of Sky Glass at an exclusive rate
• A generous pension package
• Private healthcare
• Discounted mobile and broadband
• A wide range of Sky VIP rewards and experiences

Inclusion & how you'll work

We are a Disability Confident Employer, and welcome and encourage applications from all candidates. We will look to ensure a fair and consistent experience for all, and will make reasonable adjustments to support you where appropriate. Please flag any adjustments you need to your recruiter as early as you can.

Your Office Space

Osterley Campus – a 10‑minute walk to Syon Lane train station. Shuttle buses run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. On‑campus amenities include 13 subsidised restaurants, cafés, a Waitrose, gym, cinema and beauty salon.

Apply

Inventive, forward‑thinking minds come together to work in Tech, Product and Data at Sky. It's a place where you can explore what if, how far, and what next. If you believe in better, we'll back you all the way. Just so you know, if your application is successful, we may ask you to complete a criminal record check. Depending on the role and nature of any convictions you may have, we might have to withdraw the offer.