Staff Machine Learning Engineer

Staff Machine Learning Engineer

Competitive salary up to £140,000- £210,000 + bonus London based (1 day in office per month)

This is a global technology group with an R&D team that moves fast and thinks big. They're exploring how AI can raise the quality and performance of large-scale digital products, blending hands-on engineering with real research. If you enjoy trying new ideas, you'll fit in perfectly.

THE COMPANY

This is a global tech organisation with a dedicated R&D function exploring how AI can improve the quality, reliability, and performance of large-scale digital experiences. The team works on forward thinking projects that blend research, experimentation, and hands-on engineering.

THE ROLE

As a Staff ML Engineer, you'll take the lead on projects focused on anomaly detection in video based or interactive environments. You'll guide technical direction, support junior engineers, run experiments, and ship models into production.

Specifically, you can expect to be involved in the following:

• Building and improving ML models for anomaly detection
• Leading research work streams
• Scoping, planning, and communicating project direction with stakeholders
• Mentoring juniors
• Working across areas like self supervised learning, multi modal, or vision-language models
• Bringing concepts to life: from research ? prototype ? production

SKILLS & EXPERIENCE

You'll thrive in this role if you have:

• Experience leading technical delivery or mentoring junior ML engineers
• Strong hands-on ML skills in Python and frameworks like PyTorch or TensorFlow
• A background in anomaly detection, computer vision, or video based ML
• Experience taking ML research or prototypes through to real world deployment
• Either a research grounding (publications, research-led roles) or deep knowledge of gaming/interactive systems

BENEFITS

• Competitive salary
• 1 day per month in the office
• Sponsorship available
• Great feedback and clear process

HOW TO APPLYPlease register your interest by sending your resume to Madison Barlow via the Apply link on this page.