Job Search and Career Advice Platform

Enable job alerts via email!

Lead ML Engineer: Personalisation & Pipelines (Hybrid)

Sky

Leeds

Hybrid

GBP 60,000 - 80,000

Full time

2 days ago
Be an early applicant

Generate a tailored resume in minutes

Land an interview and earn more. Learn more

Job summary

A leading media company in the UK is seeking a machine learning specialist to design and optimize models focused on personalization. You will construct and maintain scalable data pipelines, deploy models in production, and lead experiments. The ideal candidate has advanced Python skills, experience with machine learning frameworks, and solid analytical abilities. A hybrid work model and various perks are offered for this role.

Benefits

Private healthcare
Generous pension package
Discounted mobile and broadband
Subsidised gym membership
Sky Q and Sky Glass at an exclusive rate
Sky VIP rewards

Qualifications

  • Demonstrated expertise in the full lifecycle of machine learning.
  • Advanced proficiency in Python with knowledge of ML libraries.
  • Experience with model serving technologies.

Responsibilities

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

Skills

Machine learning lifecycle expertise
Advanced Python proficiency
Experience with ML frameworks
High-volume data processing
Recommendation system understanding
Generative AI familiarity
Analytical problem-solving skills
Mentoring abilities

Tools

TensorFlow
PyTorch
TFX
Kubeflow
Job description
A leading media company in the UK is seeking a machine learning specialist to design and optimize models focused on personalization. You will construct and maintain scalable data pipelines, deploy models in production, and lead experiments. The ideal candidate has advanced Python skills, experience with machine learning frameworks, and solid analytical abilities. A hybrid work model and various perks are offered for this role.
Get your free, confidential resume review.
or drag and drop a PDF, DOC, DOCX, ODT, or PAGES file up to 5MB.