Lead ML Engineer: Personalisation & Pipelines (Hybrid)

Sky; England; Hybrid; GBP 60,000 - 80,000; Full time

Job summary

A leading streaming service company in the UK is seeking a Machine Learning Engineer to develop and optimize models for user personalisation. You will design and maintain data pipelines and collaborate with multidisciplinary teams to align ML initiatives with business objectives. The ideal candidate has strong expertise in machine learning lifecycle, experience with Python, and a thorough understanding of recommendation systems. This role offers great benefits, including a hybrid work model and various on-site perks.

Benefits

Generous pension package

Private healthcare

Discounted mobile and broadband

Subsidised gym

Subsidised restaurants

Qualifications

• Demonstrated expertise in the full lifecycle of machine learning.
• Advanced proficiency in Python and knowledge of ML libraries/frameworks.
• Experience with high-volume data processing and real-time streaming architectures.

Responsibilities

• Design, train, and optimise machine learning models.
• Construct and maintain data pipelines for feature engineering.
• Deploy and supervise ML models in production environments.

Skills

Machine learning lifecycle expertise

Python proficiency

ML libraries/frameworks like TensorFlow and PyTorch

ML Training frameworks experience

High-volume data processing

Recommendation system design

Generative AI familiarity

Communication skills

Analytical problem-solving

Tools

TensorFlow

PyTorch

Kubeflow Pipelines

TensorFlow Serving

Job description

A leading streaming service company in the UK is seeking a Machine Learning Engineer to develop and optimize models for user personalisation. You will design and maintain data pipelines and collaborate with multidisciplinary teams to align ML initiatives with business objectives. The ideal candidate has strong expertise in machine learning lifecycle, experience with Python, and a thorough understanding of recommendation systems. This role offers great benefits, including a hybrid work model and various on-site perks.