Research Engineer - Machine Learning and Generative AI

Principle; Greater London; On-site; GBP 90,000 - 130,000; Full time

Job summary

Principle in London is seeking a Research Engineer to advance AI and machine learning research. You will be deeply embedded in a research team, building ML systems, experimenting with progress around large AI models and multi-agent setups.

The role emphasizes hands-on engineering alongside theoretical inquiry, contributing to synthetic data and reinforcement learning projects within a fast-moving environment.

Qualifications

• 2+ years hands-on Machine Learning/AI experience.
• Experience developing ML models at scale.
• Experience running complex experiments with large AI models and datasets.
• Strong understanding of the scientific/research process.
• Comfortable operating in a fast-moving, ambiguous research environment.

Responsibilities

• Build and experiment with ML systems and research infrastructure.
• Collaborate with researchers on complex AI problems.
• Investigate why approaches succeed or fail and iterate.

Skills

ML/AI experience

Large AI models

Experimentation

Research mindset

Adaptability

Education

Master's or PhD in ML/AI

Tools

PyTorch

LLMs

Reinforcement learning

Generative AI

Multi-agent systems

Job description

Research Engineer - Machine Learning & Generative AI, Global Tech

We're hiring a Research Engineer to join a world-leading technology organisation working at the forefront of AI and machine learning research. This is a rare opportunity to be deeply embedded within a research team, contributing directly to cutting-edge work around large AI models, reinforcement learning, synthetic data and multi-agent systems.

You'll combine hands-on engineering with research, building and experimenting with ML systems, developing robust research infrastructure and working alongside researchers on complex, rapidly evolving problems.

• 2+ years' hands-on Machine Learning/AI experience - including ML, artificial intelligence, recommendation systems or pattern recognition.
• Experience developing ML models at scale, ideally gained within a major technology company, AI research lab or similarly sophisticated environment.
• Experience running complex experiments with large AI models and datasets.
• Strong understanding of the scientific/research process and the ability to investigate why approaches succeed or fail.
• Comfortable operating in a fast-moving, highly ambiguous research environment where priorities can change quickly.

Experience with PyTorch, LLMs, LLM post-training, reinforcement learning, generative AI or multi-agent systems would be particularly valuable. A research-focused Master's or PhD in ML/AI is advantageous but not essential.

Deadline for this role is Monday the 14th of December