Machine Learning Engineering Lead

Sky; Walthamstow; Hybrid; GBP 100,000 - 125,000; Full time

Job summary

A leading media and entertainment company in the UK is searching for a skilled Lead Machine Learning Engineer to enhance their personalized recommendation systems. The role requires expertise in machine learning lifecycle, model development, and collaboration with data scientists and engineers. Candidates should be proficient in Python and ML frameworks and have experience with production deployments. The position offers competitive rewards and a hybrid working environment that supports creativity and innovation.

Benefits

Generous pension package

Private healthcare

Discounted mobile and broadband

Wide range of Sky VIP rewards

Access to subsidised gyms and cafés

Qualifications

• Expertise in full lifecycle machine learning from development to deployment.
• Proficiency in Python and ML libraries.
• Experience with ML training and model serving technologies.

Responsibilities

• Design and optimize machine learning models for user personalization.
• Construct scalable data pipelines for training and feature engineering.
• Deploy ML models in production ensuring optimal performance.
• Lead design and analysis of A/B tests for model evaluation.

Skills

Machine Learning Lifecycle

Python

ML Libraries (e.g., TensorFlow, PyTorch)

Data Processing

Recommendation Systems

Generative AI

Communication

Mentoring

Tools

TFX

Kubeflow Pipelines SDK

Tensorflow Serving

Triton

TorchServe

Job description

Job Overview

ID: 1854517

Date Posted: Posted 1 day ago

Location: Walthamstow

Expiration Date: 02/02/2026

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.

• 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 both structured and unstructured large‑scale 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 (eg. 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've got a few choices: head to The Pavilion for a bite with the team, pop to the onsite gym for a quick workout, or join in with a lunchtime community meetup — whatever suits you. Once you're back, you'll carry on working with your team on your current feature. Later in the afternoon, the team might fancy a quick coffee break before wrapping up the day with a team retrospective.

Global OTT Technology

Our team develops and supports market‑leading video streaming services, underpinned by state‑of‑the‑art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across Europe. No matter the device, the time or the place, we make sure that our diverse audiences can easily find and enjoy whatever they want to watch, choosing from the world's best entertainment, news and sport.

The rewards

There's one thing people can't stop talking about when it comes to LifeAtSky: the perks. Here's a taster:

• 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.

We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home. You’ll find out more about what hybrid working looks like for your role later on in the recruitment process.

Your office space

Osterley

Our Osterley Campus is a 10‑minute walk from Syon Lane train station. Or you can hop on one of our free shuttle buses that run to and from Osterley, Gunnersbury, Ealing Broadway and South Ealing tube stations. There are also plenty of bike shelters and showers.

On campus, you’ll find 13 subsidised restaurants, cafés, and a Waitrose. You can keep in shape at our subsidised gym, catch the latest shows and movies at our cinema, get your car washed, and even get pampered at our beauty salon.

We’d love to hear from you

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.

But better doesn't stop at what we do, it's how we do it, too. We embrace each other's differences. We support our community and contribute to a sustainable future for our business and the planet.

If you believe in better, we'll back you all the way. Just so you know: if your application is successful, we'll ask you to complete a criminal record check. And depending on the role you have applied for and the nature of any convictions you may have, we might have to withdraw the offer.