Staff & Principal Machine Learning Engineer

Tubi; York and North Yorkshire; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

Healthcare Coverage

Competitive Compensation

Family Support

Wellness Programs

Continuing Education

Financial Support

Job summary

Tubi is seeking a Senior Machine Learning Engineer in the United Kingdom to drive the design, development, and deployment of advanced recommendation systems at scale for a global audience.

You will work closely with Product, Engineering and Data Science teams to ensure robust ML pipelines, from data extraction to model deployment, delivering high-quality user experiences.

Qualifications

• Deep learning experience for recommendation systems.
• 8+ years of industry experience in ML systems.
• Strong statistical knowledge: hypothesis testing, regression, performance metrics.
• Ability to deep dive into components and understand architecture of ML solutions.
• Proficiency in building and deploying full-stack ML pipelines.

Responsibilities

• Design, develop and implement advanced recommender algorithms at scale.
• Lead ML pipeline development: data extraction, feature development, model training, testing and deployment.
• Monitor and optimize deployed models to meet business goals and user experience metrics.
• Collaborate with Product, Engineering and Data Science to align requirements and deliver ML-driven solutions.

Skills

Deep learning

Recommendation systems

Data pipelines

Model evaluation

Education

MSc or PhD in Computer Science / ML / Statistics / Mathematics

Tools

TensorFlow

PyTorch

Job description

• We are seeking a highly skilled Machine Learning Engineer to contribute to transformative projects in video personalization
• In this role, you will design and implement advanced algorithms and systems to improve our personalization strategy
• As a senior technical expert, you will tackle complex problems in machine learning at scale, collaborating closely with cross‑functional teams to develop and optimize machine learning‑driven solutions
• Lead the design, development, and implementation of advanced recommendation systems and algorithms for a global audience
• Conduct deep dives into algorithmic components and systems, ensuring that models are optimized for both performance and scalability across multiple regions and product areas
• Build and deploy high‑impact robust ML pipelines, including data extraction, feature development, model training, testing, and deployment
• Continuously monitor, evaluate, and optimize the performance of deployed models, ensuring they meet business goals and provide high‑quality user experiences
• Work closely with Product, Engineering, and Data Science teams to align on product requirements, set expectations, and deliver machine learning‑driven solutions that improve user engagement

Benefits

• Healthcare Coverage: We offer medical, dental, and vision coverage, effective from day one.
• Competitive Compensation.
• Family Support: We’re proud to support families of all kinds, and offer generous parental leave, childcare support, and eldercare assistance whenever you need it.
• Wellness Programs: Monthly wellness reimbursement, generous time off, and additional Tubi Holidays help us support mental and physical wellbeing for you and your family.
• Continuing Education: From education reimbursement to leadership development to certification support, we’re invested in developing our talent so you can take your career to the next level.
• Financial Support: We offer resources to help keep you financially fit and invested in your future, from our highly‑rated retirement savings matches to financial advisors and planning services.

Experience with deep learning technologies for recommendation systems, including TensorFlow, PyTorch, or similar frameworks8+ years of industry experience building production Machine Learning systemsSolid understanding of statistical concepts such as hypothesis testing, regression analysis, and performance evaluation metrics for machine learningAbility to deep dive into individual components and systems, as well as understand the overall architecture of machine learning solutionsProficiency in building and deploying full‑stack machine learning pipelines: data extraction, data mining, model training, feature development, testing, and deploymentMSc or Ph.D. in Computer Science, Machine Learning, Statistics, Mathematics, or a related field