Artificial Intelligence Researcher

microTECH Global LTD; England; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A leading tech consultancy is seeking an AI Researcher to develop and refine algorithms for generative models. Candidates should have a PhD in Computer Science or a related field and deep expertise in Reinforcement Learning. Responsibilities include designing experiments and publishing findings in top-tier AI conferences. The position is full-time with hybrid working options available in Cambridge or London, offering the opportunity to work at the intersection of RL, LLMs, and generative modeling.

Qualifications

• PhD required in a relevant field.
• Publications in top-tier AI conferences preferred.
• Strong expertise in Reinforcement Learning and generative models.

Responsibilities

• Develop and refine RLHF algorithms for models.
• Implement deep reinforcement learning methods.
• Train and evaluate LLMs and diffusion models.
• Design experiments for model alignment.
• Collaborate with teams on alignment pipelines.
• Publish findings in AI conferences.

Skills

Reinforcement Learning (policy optimisation)

Deep Learning (PyTorch, JAX, TensorFlow)

Python proficiency

Probability and statistics

Education

PhD in Computer Science or Machine Learning

Tools

PyTorch

JAX

TensorFlow

Job description

This range is provided by microTECH Global LTD. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.

Base pay range

Direct message the job poster from microTECH Global LTD

Software and IT Consultant at microTech Global LTD

Job Title: AI Researcher

Location: Cambridge or London, UK

This is a permanent position with candidates required to do hybrid working in either Cambridge or London.

Our client are looking for AI Researchers specialising in Reinforcement Learning with Human Feedback (RLHF) and Generative AI. In this role, you will design and optimise the algorithms that align large-scale generative models with human preferences, ensuring they are safe, controllable, and capable of producing high-quality outputs across multiple modalities. You’ll sit at the intersection of RL, LLMs, and generative modelling, helping us build the next generation of foundation models.

Responsibilities

• Develop and refine RLHF algorithms for large language and generative models.
• Research and implement deep reinforcement learning methods (policy gradients, actor‑critic, off‑policy learning) for model alignment.
• Train, fine‑tune, and evaluate LLMs and diffusion models at scale.
• Design experiments to align generative outputs with human and organisational preferences.
• Collaborate with researchers, engineers, and human feedback teams to build scalable alignment pipelines.
• Publish findings in top‑tier AI conferences and contribute to open‑source frameworks.

Key Requirements

• PhD in Computer Science, Machine Learning, or related field.
• Publications at NeurIPS, ICML, ICLR, ACL, or related venues.
• Deep expertise in Reinforcement Learning (policy optimisation, reward modelling, RLHF).
• Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow).
• Proficiency in Python and standard ML libraries.
• Solid foundations in probability, optimisation, and statistics.
• Experience working with large‑scale distributed training on GPUs/TPUs.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Software Development, IT System Custom Software Development, Semiconductor Manufacturing

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