Machine Learning Jobs

• York
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship taking complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, plus Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role within 20 miles of their location, with training designed to fit around existing work or unemployment.

Azure · Microsoft AI-900 · Git +1

• Worcester
• £25,000 – £45,000 pa
• Entry level

A self-paced traineeship taking complete beginners through AI fundamentals, Python, data handling, machine learning and Git/GitHub, plus Microsoft AI-900 certification and two tutor-assigned industry projects. On completion, candidates are placed into a Junior AI Engineer role within 20 miles of their location, with training designed to be completed in 6-12 months around existing work or study.

Microsoft AI-900 · Azure AI Fundamentals · Git +1

• London
• Hybrid
• Permanent

Optimises large language model training performance, focusing on throughput and accelerator utilisation. Writes low-level CUDA and Triton kernels, works on distributed training strategies, and builds profiling tools within the Pre-Training team. Combines software engineering, ML and kernel design to remove performance bottlenecks.

JAX · PyTorch · XLA +4

• London
• Remote
• Permanent

Designs and writes high-performance, scalable software for training frontier models, improving the training setup from an infrastructure and codebase performance standpoint. Builds tooling to speed up training cycles and works on supercompute and data infrastructure, bridging research and production. Works with distributed training stacks like Kubernetes, Slurm and Ray, with one of the highest compute-to-engineer ratios in the world.

JAX · PyTorch · XLA +4

• Leicester
• Remote
• £30,000 – £45,000 pa
• Junior

A 15-step online, self-paced traineeship covering AI engineering fundamentals, Python, data handling, prompt engineering, RAG, machine learning and AWS cloud certification, with tutor and recruitment support. It is a paid training course rather than a salaried job, aimed at career changers with no prior experience, and includes a job guarantee or money-back promise.

Jupyter Notebooks · VS Code · Streamlit +7

• Manchester
• Remote
• £30,000 – £45,000 pa
• Junior

A 15-step online, self-paced AI traineeship covering Python, NumPy, Pandas, scikit-learn, Hugging Face, prompt engineering, RAG and vector databases, culminating in an AWS Certified Cloud Practitioner exam. It is a paid training course with fees, offering 1-to-1 tutor and recruitment support plus a job guarantee, rather than a salaried position.

Jupyter Notebook · VS Code · Streamlit +7

• London
• Hybrid
• Mid-level

Owns PX's editorial calendar and writes blog posts, web pages, thought leadership, scripts and event materials, translating deep technical work into clear narratives. Leads LinkedIn and Instagram, supports executive and technical speaking engagements, and partners with Talent on employer brand storytelling. Works cross-functionally with engineers, designers and external agencies in a fast-moving, high-ownership comms team.

LinkedIn · Instagram · Figma +1

• Manchester
• Hybrid
• £48,337 – £59,390 pa
• Mid-level
• Contract

Develops and applies machine-learning and AI methods to protein engineering and enzyme design, analysing large biological, chemical and experimental datasets and building predictive models and computational tools. Works within an interdisciplinary group spanning the Manchester Institute of Biotechnology and Department of Chemistry, providing ML and data-science expertise, training and support to postdocs and students, and contributing to publications and funding bids.

• London
• Permanent

Conducts research on safety post-training methods such as RLHF, RLAIF, DPO, PPO, reward modeling, adversarial training and synthetic data, then builds evaluations for harms like jailbreaks, hallucination and unsafe tool use. Highly cross-functional, partnering with core training, product, policy, legal and trust and safety teams to ship safety improvements into production models.

OpenAI

• London
• On-site
• Mid-level
• Permanent

This role involves conducting advanced research to identify systematic anomalies in the equities market, developing and implementing trading strategies, and maintaining portfolio trading systems. You will work with large datasets, perform alpha idea generation, and contribute to the scalable research framework.

• London
• On-site
• Mid-level
• Permanent

As a Quantitative Researcher, you will develop and test innovative signals, models, and trading strategies for global financial markets. You'll work closely with a small, high-performing team to design and implement research tools and data pipelines, applying rigorous statistical and computational methods.

• London
• Hybrid
• Lead · manages people
• Permanent

Builds and leads the technical programme management function for Wayve's AI Platform organisation, owning planning, prioritisation and execution across data and compute infrastructure, developer tooling, training technology and inference optimisation. Coaches a small TPM team, manages cross-team dependencies with ML, research, embedded and vendor partners, and drives measurable gains in developer velocity, compute efficiency and model performance.

Kubernetes · Ray · Flyte +6

• United Kingdom
• Entry level
• Internship

Six- to twelve-month AI and algorithms internship for PhD or Master's students, working alongside engineers on client projects involving modelling, training, testing and data wrangling. Interns also contribute to internal R&D, building on state-of-the-art AI literature, and present results to colleagues and clients. Requires strong Python, Git and demonstrable research experience, plus UK security clearance eligibility.

Git · Transformer Models · Diffusion Models +1

• London
• Hybrid
• Senior
• Permanent

Owns the end-to-end release cycle for AI driving models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

GitHub · Buildkite · CLI

• Cranfield
• £21,805 pa
• Entry level
• Contract

A PhD studentship researching AI-on-RAN, optimising distributed and mobile inference of large language models by adapting token, memory and bandwidth use in real time. The work sits across AI and telecoms, with training alongside other PhD students in the EPSRC Future Telecommunications Hubs network and exposure to defence, government and infrastructure stakeholders.

AI-on-RAN · 6G