Artificial Intelligence Jobs

• Southampton
• Hybrid
• £41,064 – £45,064 pa
• Contract

Embed physics-informed generative AI tools into a marine vessel concept, generation and evaluation platform as part of a Knowledge Transfer Partnership between Compute Maritime Ltd and the University of Southampton. Develop and validate fast physics-informed models for ship resistance, propulsion and energy efficiency using CFD and benchmark data, and integrate multidisciplinary optimisation methods into the NeuralShipper platform.

PyTorch · TensorFlow · JAX +2

• San Francisco, United States
• Hybrid
• US$150,000 – US$190,000 pa
• Mid-level

Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point-cloud and mesh data, selecting frameworks, and translating R&D outputs into reusable libraries and products. Requires travel of 3-4 weeks per quarter to customer sites across multiple continents.

TensorFlow · MLflow · Spark +6

• New York, United States
• Hybrid
• US$150,000 – US$190,000 pa
• Mid-level

Builds and deploys machine learning pipelines for industrial physics applications, working directly with customers on-site to embed AI models into practical tools. Involves manipulating 3D point cloud and mesh data, cloud and HPC environments, and translating R&D outputs into reusable libraries and products. Requires frequent travel to customer sites across multiple continents.

TensorFlow · MLflow · Spark +6

• Cambridge
• On-site
• £40,000 – £70,000 pa
• Mid-level
• Permanent

Work across the full machine learning lifecycle, from concept and architecture through data collection, training, integration and testing, with models embedded in in-house electronics to produce prototype and demonstrator devices. Projects span computer vision, generative models and novel methods across multiple domains, in a low-management, collaborative team.

TensorFlow · PyTorch · CUDA +2

• Sydney, Australia
• Hybrid
• Mid-level
• Permanent

Deliver bespoke, production-grade machine learning systems for clients across government, finance, retail and defence. The role spans building and deploying ML software and infrastructure, defining deployment standards, and leading technical scoping and architecture decisions while advising non-technical stakeholders.

Scikit-learn · TensorFlow · PyTorch +5

• London
• On-site
• Entry level
• Permanent

Builds and maintains scalable training and inference pipelines for biological foundation models such as Transformers and SSMs, optimising latency and throughput. Works with researchers and product engineers to turn notebooks into production systems, owning ML infrastructure like data loading, distributed compute and experiment tracking while prototyping post-training methods.

• London
• Hybrid
• Senior
• Permanent

Post-train, distill and evaluate GAIA-family large video diffusion world models for synthetic driving data, covering embodiment and pose transfer. Own large-scale GPU generation pipelines and land synthetic data into the driving-model training stack, working between ML research and platform engineering.

PyTorch · GAIA · CUDA +1

• London
• Hybrid
• Senior
• Permanent

Architect novel generative models to design functional proteins, working in an interdisciplinary team of ML researchers, protein engineers and biologists. The role spans data curation, evaluation metrics, rapid prototyping, cloud training and inference, and planning wet lab testing campaigns, with about 10% of time for self-development.

• London
• Hybrid
• Permanent

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.

Scikit-learn · TensorFlow · PyTorch +5

• Manchester
• Senior

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.

PyTorch · GCP · Docker +4

• London
• Hybrid
• £600 – £650 pd
• Contract

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.

Azure · TensorFlow · PyTorch

• Brentford
• Hybrid
• £75,000 – £100,000 pa
• Mid-level
• Permanent

Develop an engineering-grade Spiking Neural Network engine for machine vision, turning research outputs into production C++ software. Work alongside researchers, data scientists and engineers on SNNs, CNNs, Transformers, synthetic training data and ISR imagery, with system design, testing and CI/CD responsibilities.

PyTorch · CUDA · CNNs +2

• London
• On-site
• Senior
• Permanent

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.

PyTorch · CUDA · Triton +1

• Cambridge
• Hybrid · 2 days in office

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.

PyTorch · TensorFlow · scikit-learn +2

• London
• Senior
• Permanent

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.