Artificial Intelligence Jobs

CrowdStrike · Romania

Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design through prototyping, implementation and production operations. Works autonomously on a distributed remote team, gathering requirements from analysts and choosing the technology stack, with existing Go and Python codebases to maintain.

CrowdStrike · United Kingdom

Builds and operates large-scale data processing pipelines, storage systems and presentation layers for the Intelligence team, owning systems from design and prototyping through production deployment and long-term maintenance. Works fully remotely with analysts as internal customers, choosing your own tech stack across Go, Python, SQL/NoSQL and cloud.

PhysicsX · Singapore

Builds physical foundation models for industrial engineering, scaling training across multi-GPU cloud compute and turning research prototypes into robust, optimised implementations. Works closely with research scientists, simulation engineers and customers, owning research work-streams and translating results into reusable libraries, tooling and products.

eFinancialCareers · London

Design and build an agentic automation framework in Python on AWS Bedrock, decomposing Jira workflows into microservices and LLM agents. Own end-to-end delivery of automation across Operations, Compliance and Risk, including secure integrations, prompt strategies and retrieval augmentation, while mentoring junior engineers and driving CI/CD standards.

Entrust · London

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, and mentors engineers within a squad-based team.

PhysicsX · New York, United States · US$200,000 – US$250,000 pa

Owns deployment of ML models and engineering surrogates (deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization) into customer production environments, building scalable training and inference pipelines and APIs on cloud and on-prem. Leads scoping and architecture design, mentors engineers and data scientists, and travels to customer sites roughly 3-4 weeks per quarter to embed AI models on-site.

Entrust · Lisbon, Portugal

Builds and operates production ML systems for document classification and extraction, using VLM/LLMs and traditional ML to power identity verification for millions of users. Leads technical design from RFC to deployment, optimises GPU inference, and designs training, evaluation and labelling pipelines. Works in a squad-based team alongside Applied Science, Product and Data Science, mentoring engineers and driving reliability and scalability.

Infused Solutions · London · £65,000 – £75,000 pa

Senior AI EngineerLocation: Remote (UK) or Hybrid - London (1 days per week in the office if London-based)Salary: £65,000 - £75,000 + Excellent BenefitsJob Type: PermanentPlease note: Applicants must have the right to work in the UK. Unfortunately, visa sponsorship...

Faculty · London

Builds client-facing products that visualise insights from data scientists, working in cross-functional delivery teams within the National Security and AI Safety unit. Owns frontend standards and reusable component libraries across the company, sets up deployment infrastructure, and mentors other engineers. Requires React, TypeScript, ES6, HTML/CSS3 and data visualisation such as d3, with cloud exposure to AWS, GCP or Azure.

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.

Hyre Ai · London · £50,000 – £60,000 pa

Design and evolve production multi-agent systems using Anthropic, OpenAI and Perplexity models on AWS, extending the company's MCP server with new tools. Build the eval and observability layer with golden datasets, regression suites and LLM-as-judge, own AWS infrastructure (ECS Fargate, Lambda, Step Functions, Bedrock) and guard against prompt injection and PII leakage. Set technical direction and mentor engineers.

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.

CBSbutler Holdings Limited trading as CBSbutler · Uxbridge · £600 – £625 pd

Hands-on technical leadership across a major airline's Data & AI team, driving a 2026 data engineering workstream. You will design scalable AWS data pipelines, implement CI/CD and DevOps practices, and mentor data and software engineers. Snowflake and AI-assisted development experience are desirable.

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.

Tech Recruitment Specialists Ltd · London · £38,000 – £45,000 pa

Supports the development, optimisation and deployment of AI and machine learning models, working with large datasets for preprocessing and training, and helping monitor AI applications in production. Collaborates with software engineers, product teams and data specialists, contributes to backend development and API integrations, and researches new AI frameworks. Emphasis on responsible, ethical AI with bias mitigation, transparency and fairness.