Artificial Intelligence Jobs

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

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 infrastructure, and translating R&D outputs into reusable libraries and products.

TensorFlow · MLflow · Spark +6

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

Delivery-focused role embedding physics-aware AI models into customer tools, working on-site with clients across aerospace, automotive and energy. Involves building reliable ML data pipelines, manipulating 3D point-cloud and mesh data, and translating R&D outputs into reusable libraries and products. Expects travel of 3-4 weeks per quarter to customer sites worldwide.

TensorFlow · MLflow · Spark +6

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

This role involves developing end-to-end machine learning systems integrated with advanced electronics for defence and security applications. You'll work across diverse domains such as computer vision and generative models, building functional prototypes and demonstrators. The role emphasizes innovation, rapid iteration across projects, and close collaboration in a technically driven, low-management environment.

• Dublin, Ireland
• Hybrid · 2 days in office
• £388 – £474 pd
• Senior
• Contract

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.

Snowflake · AWS · Linux +2

• 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

• Remote (UK)
• Remote
• Mid-level
• Permanent

Deliver bespoke, production-grade machine learning systems for defence clients, covering the full ML lifecycle from architecture and scoping to deployment. Work with Python, Scikit-learn, TensorFlow or PyTorch, plus cloud platforms and Docker/Kubernetes, splitting time between client sites and remote work.

Scikit-learn · TensorFlow · PyTorch +5

• London
• On-site
• £150,000 – £175,000 pa
• Senior

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.

LangGraph · LangChain · FastAPI +7

• Cyprus
• Senior

Bridges research and production engineering, deploying and testing computer vision and ML systems for object tracking, automated monitoring and intelligent triaging in live environments. Involves turning research models into production-grade software, running specialised data collections and labelling, and briefing senior leadership on capability. Requires expert Python, Docker, Kubernetes and active DV clearance.

Docker · Kubernetes

• 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

• 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

• 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.

• London
• Hybrid
• Lead · manages people
• Permanent

Lead a small team iterating on Wayve's end-to-end L2 driving model, balancing hands-on Python coding and experiments with directing priorities. You'll root-cause on-road issues and fix them through data recipes, model architecture, evaluation and release readiness, working across teams on model and vehicle interface problems.

Python

• Cambridge
• Hybrid · 2–3 days in office
• Senior

Work on complex R&D projects within a Modelling Team that trains large self-supervised speech models and deploys them to production. Involves distributed training, transformer architectures, and inference optimisation, with mentoring and cross-department collaboration.

GQA · KV-Caching · Flash Attention +2