Senior Machine Learning Engineer

A major global technology company is investing heavily in an R&D initiative aimed at transforming how large‑scale virtual environments are analysed, validated, and improved. They are seeking a Senior Machine Learning Engineer to join a highly technical applied research team working on automated anomaly detection for interactive digital worlds.

This team works across research, prototyping, and applied engineering, tackling challenges involving video understanding, real‑time systems, simulation, and complex behaviours. If you enjoy pushing ML beyond traditional datasets and into rich, dynamic, unpredictable spaces, this role offers an unusual blend of creativity and impact.

Location: London (approx. 1 day per month onsite)
Compensation: £90k‑£100k + bonus

You’ll contribute to building an intelligent agent system that can autonomously explore digital environments and surface anomalies ranging from visual defects to unexpected gameplay behaviours. This involves models that can learn structure, context, and semantic understanding of highly diverse scenes.

Your work will include:

• Designing and training anomaly‑detection models tailored for video, visual streams, or simulated data.
• Working on components that contribute to autonomous traversal, content understanding, and error detection.
• Prototyping new concepts across self‑supervised learning, multimodal embeddings, or CV architectures.
• Collaborating closely with research scientists, software engineers, and domain specialists.
• Taking part in a research‑driven culture where experimentation and curiosity are encouraged.
• Providing technical guidance and practical mentorship to junior engineers.

This role suits engineers who love solving challenging ML problems in visually rich environments. We’re looking for someone who has:

• Strong hands‑on ML engineering experience - ideally with video, image sequences, or visual analytics.
• Exposure to anomaly detection, real‑time analysis, simulation, or sequential modelling.
• Experience with end‑to‑end ML development: data, modelling, prototyping, evaluation, iteration.
• Curiosity or passion for game‑like or simulation‑based environments (not required, but helpful).
• Familiarity with research concepts, academic papers, or experimental methodologies.
• The ability to work in an exploratory, research‑heavy environment with evolving priorities.

Apply with the link below!