Senior Machine Learning Engineer (Recommendation)

Sky; Isleworth; Hybrid; GBP 80,000 - 100,000; Full time

Benefits offered by this job

Sky Q

Exclusive Sky Glass rate

Generous pension package

Private healthcare

Discounted mobile and broadband

Sky VIP rewards

Job summary

Sky is seeking a Senior Machine Learning Engineer in Isleworth to enhance our recommendation systems. This role involves model development, data pipeline engineering, and the deployment of ML models ensuring optimal performance for millions of users.

The ideal candidate should possess in-depth knowledge of the ML lifecycle, be proficient in Python, and have experience with tools like TensorFlow and Kubeflow. A commitment to cross-functional collaboration is essential in a hybrid work environment that values innovation and inclusion.

Qualifications

• Demonstrated expertise in machine learning model development and deployment.
• Strong proficiency in Python and ML frameworks.
• Experience in mentoring junior engineers.

Responsibilities

• Design, train, and optimise machine learning models.
• Construct and maintain scalable data pipelines.
• Deploy and supervise ML models in production.

Skills

Machine Learning full lifecycle expertise

Proficiency in Python

Experience with ML libraries/frameworks (TensorFlow, PyTorch)

Experience with ML Training frameworks

High-volume data processing

Tools

TensorFlow Serving

Kubeflow Pipelines SDK

Job description

What You'll Do

We are seeking a highly skilled Senior 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: 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.
• Strong 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

At the start of the day, you will join the team stand‑up and then choose a task to work on. Throughout the day, you’ll collaborate with team members and work on your current feature. You’ll also have opportunities for coffee breaks and team retrospectives.

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.

We've embraced hybrid working and split our time between unique office spaces and the convenience of working from home.

Additional Information

If your application is successful, we will ask you to complete a criminal record check and, depending on the nature of any convictions you may have, we might have to withdraw the offer.