Artificial Intelligence Jobs

Luminance · Cambridge

Join a small, dynamic R&D team prototyping and implementing new approaches to AI problems, evaluating output quality, efficiency and feasibility against other techniques in a data-driven way. Work spans data science on large datasets, modelling and evaluation, using Python ML frameworks such as PyTorch, TensorFlow and Scikit-Learn. Open to graduates as well as senior candidates with published work in NLP, Computer Vision or Deep Learning.

Reperio Human Capital · Dublin, Ireland · £388 – £474 pd

Hands-on engineering role owning AI/ML initiatives end-to-end, from solution design and experimentation through deployment, monitoring and optimisation. Involves building production ML and GenAI solutions including RAG architectures, working with Snowflake and cloud data platforms, and developing Python and R software with strong MLOps, CI/CD and DevSecOps practices. Collaborates with data, product and business teams to turn ambiguous problems into scalable, secure solutions.

University of Essex · Ipswich · £40,000 – £45,000 pa

A KTP Associate role embedded at Distag QCS in Ipswich, working with a large, messy ERP dataset never designed for machine learning. The post holder shapes the data, builds reliable models, and leads the introduction of data-driven decision making in a business with no existing in-house data science capability. It blends hands-on Python development with change management, communication and academic paper contributions.

Faculty · London

Deliver bespoke, production-grade machine learning systems for government and national security clients, covering the full ML lifecycle from scoping and architecture to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, while advising stakeholders and defining standards for deploying ML at scale.

C4S Search Ltd · London · £600 – £650 pd

Designs, builds and deploys machine learning models into production, with a focus on recommendation systems such as personalised product recommendations, ranking and search optimisation. Works with data scientists, engineers and product stakeholders, maintaining MLOps pipelines for CI/CD, model versioning and monitoring on Azure, and retraining models to sustain accuracy on large-scale datasets.

Faculty · London

Builds and deploys production-grade machine learning systems for national security and AI safety clients, including LLM applications, multi-agent tooling and evaluation of frontier models. Involves technical scoping, architectural decisions, and advising stakeholders, with reusable infrastructure work alongside engineers and data scientists.

MFK Recruitment · Brentford · £75,000 – £100,000 pa

Develop an engineering-grade spiking neural network (SNN) engine for real-world machine vision applications in high-stakes environments. Translate advanced research into robust, production-ready C++ software, integrating SNNs, CNNs, and Transformers. Work closely with researchers and engineers on synthetic data generation, image analysis, and deployment in defence and security contexts.

ARM · Manchester

Lead the design and delivery of AI, machine learning, agentic AI and RAG-based solutions for a financial consultancy's client engagements. Build production-grade models with Python and PyTorch, design MLOps frameworks, CI/CD pipelines and cloud-native model serving, while mentoring engineers and shaping technical strategy.

Relation Therapeutics · London

Builds and scales generative and predictive models of cellular behaviour, implementing and optimising large neural networks and distributed training infrastructure. Acts as a bridge between ML research and production, profiling GPU workloads and optimising inference for use by data scientists and biologists on multi-modal biological data.

Sanderson · London · £550 – £700 pd

Builds, deploys and maintains machine learning models and end-to-end ML pipelines in a modern cloud environment, writing production-quality Python and SQL. Works with data scientists, analysts and engineers to take AI products from proof of concept to production, including NLP and large language model work, plus monitoring and documentation.

Harnham - Data and Analytics Recruitment · Abingdon · US$200,000 – US$225,000 pa

Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.

Darktrace · Cambridge

Conducts independent and collaborative research into language models, neural networks, statistical methods and classical machine learning, prototyping new ideas and improving existing projects. Implements models into the wider software stack, including optimised solutions for edge devices with tight latency and memory constraints, working closely with software engineers and security analysts.

Maxwell Bond · London · £150,000 – £175,000 pa

Hands-on role building LLM agent and retrieval systems on a small UK core team, reporting to the Head of Engineering. Work spans LangGraph/LangChain workflows, RAG pipelines with Qdrant and GraphRAG on Neo4j, model integration across Anthropic, OpenAI and Bedrock, plus evaluation harnesses and observability. Token cost, latency and auditability are treated as engineering constraints throughout.

Relation Therapeutics · London

Design and implement generative models that learn intervention effects from single-cell perturbation and multiomic data, focusing on counterfactual prediction, generalisation and experimental design. Work in interdisciplinary teams with experimental biologists to validate computational hypotheses and guide the highest-signal next experiments, using modern ML tooling including agentic workflows.

Scale AI · United Kingdom

Fellows join an interdisciplinary expert network and are matched to short-term AI/ML projects, ranging from evaluating models and designing experiments to building RL environments and reviewing PyTorch code. They may also co-author technical reports and research papers with Scale's research team. Engagement is fully remote, self-scheduled, with no minimum commitment.