Artificial Intelligence Jobs

NVIDIA · Bristol

Internship on NVIDIA's embedded computing team in Bristol, working with Tegra SoC, DGX Spark and the Jetson Embedded Platform. The role involves building Linux kernel and user-space software, improving the Jetson Developer Kit experience, and accelerating deep learning and neural network technologies for autonomous vehicles, robotics and analytics alongside hardware and software engineers.

Entrust · United Kingdom - Field (Onfido)

Owns test planning, coordination and execution within a cross-functional identity verification product team, covering web, mobile, backend and ML-powered journeys. Builds maintainable automated test frameworks, blends automation with exploratory testing, and mentors colleagues while improving CI/CD pipelines and release feedback loops.

Entrust · France - Field (Onfido)

Owns test planning, coordination and execution within a cross-functional identity verification product team, covering web, mobile, backend and ML-powered journeys. Builds maintainable automated frameworks and suites, mentors colleagues, and leads quality initiatives across engineering teams. Combines automation with exploratory testing and works with TypeScript, Ruby, Python, Playwright, Cypress and CI/CD pipelines.

NVIDIA · Bristol

Research and develop techniques to GPU-accelerate leading high performance computing applications across scientific computing, computational engineering and data science. The intern performs in-depth analysis and optimisation for current and next-generation GPU architectures, working with application developers and collaborating with architecture, research, libraries, tools and system software teams.

Anthropic · London · £225,000 – £255,000 pa

Serve as a trusted technical advisor to high-growth startups building on the Claude Developer Platform, leading deep engagements that include pair programming, architecture reviews, and code contributions. Develop evaluation frameworks, prototypes, and technical documentation, and feed patterns back to Product and Engineering. Requires production LLM application experience and frequent travel to customer sites.

Wayve · London

Owns the end-to-end release cycle for autonomous-driving AI models, coordinating ML engineering, evaluation, data science, platform, testing and product teams. Defines release gates and promotion criteria from training through validation to fleet deployment, drives regression investigations and rollback decisions, and builds tooling and KPIs to remove bottlenecks in a non-deterministic ML environment.

Databricks · London

Customer-facing engineering role building and productionizing data and AI solutions on the Databricks platform for emerging enterprise and digital native accounts. You own architecture and design decisions, implement end-to-end systems spanning data engineering, ML/AI and application development, and embed with client teams. Billable delivery work with roughly 20% travel.

Databricks · London

Customer-facing engineering role owning architecture and design decisions while building production-grade data, AI and application systems on the Databricks platform. You embed with client teams, from technical ICs to executives, to scope and deliver end-to-end solutions, contributing reusable accelerators and product feedback. Requires hands-on coding in Python, Scala or TypeScript, deep Apache Spark and distributed computing expertise, and multi-cloud knowledge, with around 20% travel to customer sites.

OpenAI · London

You'll partner with early-stage startups to embed Codex into their software workflows, building integrations, automations and reusable tools while troubleshooting technical blockers. A large part of the role is outward-facing: leading technical talks, live demos, workshops and hackathons, then feeding developer insights back to OpenAI's product and research teams.

CrowdStrike · Canada - Remote ON · CA$150,000 – CA$200,000 pa

Lead a growing team of engineers building self-service infrastructure-as-code primitives, architecting large-scale core services, and driving cloud cost optimization across a multi-cloud environment. The role blends people management with hands-on technical direction, including design reviews, on-call management, and influencing engineering strategy beyond the immediate team.

CrowdStrike · USA, DC · US$140,000 – US$215,000 pa

Lead a team of engineers building self-service infrastructure-as-code primitives, high-availability platforms and cloud cost optimization across a multi-cloud environment. The role combines people management with hands-on architecture of large-scale distributed systems, using tools like Terraform, Pulumi, Chef and Python or Go.

Wayve · London

You'll design, build and operate shared infrastructure for model access, agent runtimes and observability, taking projects from problem definition through technical design, deployment and ongoing operation. Working with security, IT and engineering teams, you'll create governed access layers, reusable tooling and standards so teams can run AI agents in production without one-off infrastructure.

Medtronic · London · £76,800 – £115,200 pa

Designs, builds and maintains AWS and on-prem infrastructure used by ML engineers, data scientists and product teams, with a strong focus on Kubernetes, Helm, Terraform/OpenTofu and GitOps delivery. Also handles platform service requests, incident diagnosis and reliability improvements, working across engineering teams in a surgical AI centre of excellence.

Helsing · London

Architect and scale the deep learning frameworks and distributed training infrastructure behind defence AI systems, extending PyTorch-based tooling and optimising GPU throughput. The role spans data strategy, storage and orchestration, working cross-functionally to maximise training efficiency and developer velocity.

Profile 29 · London · £40,000 – £50,000 pa

Supports founders, developers and customer success on a fundraising SaaS platform, splitting time between customer conversations, writing product requirements, testing features and researching AI applications. Runs sprint planning, monitors feedback and performance, and helps shape 3- and 12-month roadmaps while balancing technical debt against new features.