Artificial Intelligence Jobs

• Singapore
• Senior

Builds and applies advanced thermal, chemical and multiphase CAE models in Abaqus, ANSYS or COMSOL, coupling heat transfer with fluid, diffusion and electrostatic phenomena. Works directly with customers, often on-site, instrumenting physical processes to generate validation data and integrating models into AI tools. Combines shop-floor manufacturing experience with Python/Java automation and parametric CAD.

Abaqus · ANSYS Mechanical · ANSYS Fluent +4

• New York, United States
• Hybrid · 2–3 days in office
• Senior

Builds and automates high-fidelity electromagnetic models across low- and high-frequency applications, from chip and package design to EMI/EMC, using tools like HFSS, Maxwell and CST. Works at the intersection of CAE and data science, generating simulation data to train ML surrogates, collaborating with customers and mentoring junior engineers.

Ansys HFSS · Ansys Maxwell · CST Studio Suite +7

• London
• Hybrid
• Senior
• Permanent

Lead the design, build and deployment of production-grade ML and software systems for clients across pharma, academia and MedTech. The role blends hands-on Python and cloud engineering with architecture decisions, client-facing advisory work and mentoring junior engineers. It sits within a cross-functional life sciences team focused on AI for therapy research and commercialisation.

AWS · Azure · GCP +2

• London
• Hybrid
• Mid-level
• Permanent

Build and scale AI-powered systems for public sector clients, owning the full stack from Python/FastAPI backends to TypeScript and React or Vue frontends. Work in cross-functional teams with data scientists and product managers, deploying to AWS, Azure or GCP with Docker and building data pipelines and cloud infrastructure. May require UK Security Clearance and occasional on-site work with government clients.

AWS · Azure · GCP +6

• London
• Hybrid · 3 days in office
• Senior

Lead the hardening and scaling of an inference platform serving fleets of cutting-edge ML models for scientific applications. Set strategy and roadmaps, architect next-generation services to solve scaling limits, and partner with research, product and operations teams to align infrastructure with biotech R&D cycles.

Kubernetes · Google Cloud Platform · NVIDIA GPU +1

• London
• Hybrid · 3 days in office
• Senior

Join the Computational Sciences team to design novel large-molecule therapeutics using a cutting-edge AI drug design engine. You'll develop machine learning methods to predict biologics properties from sequence, benchmark models, and analyse lab data to guide early discovery through candidate selection.

AlphaFold

• 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

• 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

• United Kingdom
• Remote
• Contract

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.

PyTorch · TensorFlow · AWS +2

• 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

• London
• Hybrid
• Senior
• Permanent

Train, debug and improve computer vision and 3D perception models for driver assistance, working across the full ML lifecycle from data and training to evaluation and iteration. The role spans latency-constrained on-car perception and large-scale offline work with lidar, maps and 3D reconstruction to build auto-labelling data flywheels.

LiDAR

• 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

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

Join the Modelling Team to train large self-supervised and transformer-based speech models, deploying them into production with strong software engineering and model-serving practices. Work on complex R&D projects, optimise inference, and mentor engineers in a hybrid London setup.

GQA · KV-caching · Flash Attention +2

• Sheffield
• Hybrid
• £32,080 pa
• Entry level
• Contract · Part time

Build and evaluate machine learning models that predict Strep A outbreak risk from multiple real-world datasets, turning them into early-warning signals. Work with clinicians and an engineering team so analyses feed into a practical public health tool, with a focus on reproducible Python and/or R analysis.

• Manchester
• £550 – £600 pd
• Contract

Contract role building and deploying production AI/ML systems, with hands-on work in Python, PyTorch and Google Cloud Platform. The engineer develops Generative AI solutions using transformer architectures, RAG and agent frameworks like ReAct, then packages and serves models via Docker, KServe and Vertex AI endpoints. Responsibilities also cover MLOps practices such as CI/CD pipelines, model registries, monitoring, drift detection and GPU cost optimisation.

GCP · Docker · KServe +3