Machine Learning Jobs in York

CureAge Therapeutics · London

Lead the computationally guided design of a lipid nanoparticle delivery platform, applying chemical and biophysical principles to optimise LNP composition and formulation. Use AI-enabled chemistry, cheminformatics, predictive models and molecular modelling to prioritise formulation components, working closely with the experimental team and founding team in a small start-up.

Hadean · London

Lead a new AI-powered defence product team, line-managing AI/ML, simulation, infrastructure and web engineers while staying hands-on in TypeScript, React and Node. You own delivery end-to-end, hiring and people development, partnering with Product and technical leads, with hybrid working one day a week in Shoreditch.

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.

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

Build and own core platform capabilities including application infrastructure, APIs and shared services, developing full stack applications in Python, React and TypeScript. Surface machine learning and predictive analytics insights through intuitive interfaces and integrate AI/LLM-powered workflows into production, making key architectural decisions within a small AI and Innovation team.

PhysicsX · London

Build the simulation side of Large Physics Models, generating multi-fidelity CFD data to train large-scale ML models. Develop solvers in differentiable or GPU-native frameworks like JAX or Warp, using commercial and open-source CFD tools, while collaborating closely with ML researchers in a research team.

PhysicsX · New York, United States · US$150,000 – US$190,000 pa

Builds and deploys machine learning systems for industrial physics challenges, designing reliable data pipelines and working with 3D point-cloud and mesh data. Partners directly with customers on-site to embed AI models into practical tools, translating R&D outputs into reusable libraries and products. Requires Python, cloud, and MLOps experience with frequent travel.

Cohere · London

Interns work across frontend, backend, full-stack or infrastructure teams, shipping user-facing product code, building API platform features, designing data pipelines and scalable ML infrastructure, and contributing to CI/CD tooling and technical documentation. Interns are treated much like full-time engineers, with autonomy and ownership over production code, supported by mentors and team leads.

Cohere · London

Research internship focused on building and training large language models, with projects spanning base model training, retrieval augmented generation, evaluation, safety, and finetuning. Interns design and implement novel research ideas, ship state-of-the-art models to production, and publish results through papers, datasets, and code.

OpenAI · London

Builds and scales the infrastructure that trains and deploys OpenAI's agentic models, spanning a novel in-house container orchestration platform, FastAPI and gRPC APIs, and Terraform-managed cloud systems. Works closely with researchers on novel training runs while scaling production agent platforms to hundreds of millions of users.

ElevenLabs · United Kingdom

Join the research team at an AI audio company, training state-of-the-art models across modalities and improving them through post-training, data curation and architectural changes. You'll design rigorous benchmarks and evaluations to judge whether new model iterations are genuinely better, working autonomously in lean, high-velocity teams.

ElevenLabs · United Kingdom

Builds and scales data pipelines from ingestion to delivery, implementing dbt best practices, data standards and quality controls. Develops self-service tooling and documentation so teams across Engineering, RevOps and Growth can access data independently, and creates AI agents to answer data questions. Works remotely within a lean, high-velocity data team.