Machine Learning Jobs

• United Kingdom
• On-site
• Entry level
• Permanent

This role involves tackling diverse technical challenges across healthcare, defence, and energy sectors by applying physics-based problem solving to real-world engineering projects. You'll work on cutting-edge systems such as holographic imaging, ultrasonic measurement, and magnetic positioning, combining lab work with simulation and analysis. The position emphasizes rapid learning, innovation, and collaboration within a supportive, R&D-driven environment.

• United Kingdom
• On-site
• Senior
• Permanent

This role involves designing and solving complex digital electronics challenges across diverse industries such as defence, healthcare, and telecommunications. You'll lead high-speed electronics development, work on cutting-edge FPGA and processor-based systems, and debug hardware using advanced tools and in-house labs. The role emphasizes innovation, technical ownership, and collaboration within multidisciplinary teams on novel, non-repetitive projects.

• London
• Hybrid · 3 days in office
• Lead

Builds and evolves a large-scale ML infrastructure platform that supports training and deploying novel models across vast compute and data pools. Works closely with engineering, research and product teams, and explores deploying agents to improve platform robustness. Requires strong Python and experience scaling complex systems, with ML or Kubernetes exposure a plus.

Kubernetes · Google Cloud Platform · GCP

• Cambridge, United States
• Hybrid · 3 days in office
• Senior · manages people

Lead computational drug design programs from hit identification through to candidate nomination, applying AI-first approaches and shaping the ML drug design engine alongside ML scientists. Roles span Program Lead or Computational Chemistry Lead, with some positions managing 2-3 computational chemists. Hybrid working in Cambridge, MA, three days a week in office.

REINVENT

• London
• Hybrid
• Senior
• Permanent

Owns reliability of large-scale GPU, Kubernetes and distributed AI training infrastructure, turning recurring operational problems into durable engineering solutions. Improves observability, automation, deployment safety, capacity planning and incident learning, and builds GitOps delivery with Argo CD or Flux. Works across AI Platform, Compute & Data Platform and Cloud Infrastructure teams.

Kubernetes · Argo CD · Flux +2

• London
• Hybrid
• Senior
• Permanent

Develops next-generation generative world models and planners such as GAIA, simulating complex driving environments for faster training and scalable deployment. Works across diffusion, transformer and hybrid architectures, optimising inference latency and building interactive models for reinforcement learning and safety evaluation. Involves setting technical direction, mentoring researchers and publishing at top venues.

PyTorch · GAIA · Transformer +1

• Reading
• Remote
• £90,000 – £110,000 pa
• Lead

Hands-on senior role designing and building scalable data platforms, ETL/ELT pipelines and Data-as-a-Service capabilities that power analytics, machine learning and AI products for enterprise clients. Involves setting standards for data quality, governance and observability, plus secure data services and APIs, with scope to build and lead a wider data function.

AWS

• Cambridge
• Remote
• £85,000 – £100,000 pa
• Lead

Hands-on senior role designing and building scalable data platforms, ETL/ELT pipelines and Data-as-a-Service capabilities that power analytics, machine learning and AI products for enterprise clients. Involves setting standards for data quality, governance, lineage and observability, plus secure data services and APIs, with scope to build and lead a wider data function.

AWS

• Loughborough
• Hybrid · 3 days in office
• Lead
• Permanent

Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. The role combines technical direction-setting, stakeholder collaboration and mentoring, taking models from prototype through to production in a hybrid Nottingham-based team.

PyTorch · TensorFlow · Hugging Face Transformers +1

• Lincoln
• Hybrid · 3 days in office
• Lead
• Permanent

Lead the development of proprietary deep learning models to enhance underwriting capabilities, building neural networks such as LSTMs, RNNs and Transformers on structured and unstructured data. The role combines technical direction-setting, stakeholder collaboration and mentoring junior team members, taking ideas from prototype through to production.

PyTorch · TensorFlow · Hugging Face Transformers +1

• Edinburgh
• Hybrid
• Lead
• Permanent

Builds machine learning recommendation systems that match job seekers to roles and recruiters to talent across Amazon Jobs and internal hiring platforms. Works on representation learning, reinforcement learning and probabilistic modelling at global scale, with a focus on fairness and explainability, alongside engineers, scientists and product managers through the full development lifecycle.

• Kraków, Poland
• Hybrid · 2 days in office
• Senior
• Permanent

Senior ML engineer role in a cross-craft data science team building prediction, ranking and personalisation systems for an e-commerce platform. Owns the full ML lifecycle on production systems, from experimentation and training to serving, monitoring and cost management, while coaching others and shaping reusable platform building blocks.

GCP · Vertex AI · BigQuery +6

• New York, United States
• Hybrid
• US$150,000 – US$250,000 pa
• Senior

Build and deploy customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. The role spans rapid prototyping, backend development with Python/FastAPI microservices, and cloud deployment using Kubernetes, Terraform and AWS/Azure, with frequent on-site travel to customer sites.

FastAPI · Helm · Kubernetes +3

• London
• Hybrid · 3 days in office
• Senior
• Permanent

Builds and operates production ML systems for document classification and extraction, using LLMs/VLMs and traditional ML to process government identity documents at scale. Owns features from RFC through deployment, optimising GPU inference and training/evaluation pipelines in a Python, AWS and Kubernetes stack, while mentoring engineers and leading technical design.

TensorFlow · PyTorch · Triton +5

• New York, United States
• US$150,000 – US$250,000 pa

Builds and deploys customer-facing applications that put physics AI models into production, working directly with customers, data scientists and ML engineers. Involves rapid prototyping, RESTful APIs in Python (FastAPI), microservices, and cloud deployment with Kubernetes, Helm, Terraform and AWS/Azure, plus quarterly on-site travel.

FastAPI · Helm · Kubernetes +3