Artificial Intelligence Jobs

OpenAI · London

Backend engineering role building and operating the distributed systems behind ChatGPT at significant scale. You'll write production code, design shared services and APIs, lead infrastructure migrations, and own production behaviour through monitoring, staged rollouts and incident response. Combines backend development with reliability and on-call work, closely partnered with product teams.

Faculty · Remote (UK)

Lead backend and edge/IoT engineering for high-stakes Defence projects, bridging proof-of-concept work and robust production systems. You will mentor a squad of engineers, design complex components, and build CI/CD and containerisation pipelines with Docker and Kubernetes while shipping Python and compiled-language code alongside ML engineers and data scientists.

Faculty · London

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.

PhysicsX · New York, United States · US$150,000 – US$190,000 pa

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.

Experis · London · £600 – £644 pd

Builds production-grade GenAI and Agentic AI products within a product squad, using LLMs, RAG and agentic workflows. Requires strong Python engineering plus LangGraph, vector search, evaluation and Azure AI services to deliver secure, maintainable AI applications.

PhysicsX · Singapore

Lead the deployment of ML models and engineering surrogates—deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, and optimisation—into customer production environments. Own scoping, architecture, and success metrics for data/ML systems built with Python, PyTorch, Pandas, fastAPI, Scipy, and Kubeflow across cloud and on-prem. Mentor engineers and data scientists while travelling 3-4 weeks per quarter to customer sites worldwide.

Wayve · London

Lead the technical direction for an offline 3D reconstruction system that turns raw vehicle sensor data into quality-assessed 3D ground-truth geometry and ego motion. The role spans SLAM, lidar point-cloud registration, state estimation and sensor fusion, with responsibility for architecture, roadmaps, prototypes and cross-functional alignment across perception, calibration and validation teams.

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.

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.

Helsing · Berlin, Germany

Integrates state-of-the-art AI and software into complex customer systems, working directly with avionics engineers and partners to understand unfamiliar data structures, APIs and network protocols, then building adapters to connect them to Helsing's cloud infrastructure. Owns delivery end-to-end, from formalising requirements and fixing bugs to shipping features and running technology demonstrations in simulations or on real systems.

Harnham - Data and Analytics Recruitment · Abingdon · US$200,000 – US$225,000 pa

Build scalable data platforms, pipelines and ML infrastructure, and deploy production AI solutions including LLMs, RAG systems and AI agents. Work in a small, highly visible team partnering with investment and operational stakeholders, owning projects end-to-end from design through production and driving architecture decisions.

Harnham - Data and Analytics Recruitment · London · £80,000 – £85,000 pa

Design, build and deploy scalable AI and machine learning solutions from concept to production, including Generative AI applications using LLMs and orchestration frameworks. Write production-grade Python, apply MLOps practices such as CI/CD, containerisation and monitoring, and build data pipelines for training, fine-tuning and inference. Work hybrid in London alongside data scientists, engineers and business stakeholders on large-scale datasets.

Relation Therapeutics · London

Join the Platform Team to design and scale Kubernetes-based hybrid compute clusters across private and public clouds, building core platform services and APIs. You will own CI/CD pipelines, monitoring, backup and disaster recovery, and work closely with Machine Learning and Data Science teams to support their computational needs.

eFinancialCareers · London

You will partner with portfolio managers, analysts and researchers to understand investment workflows, then design, build and deploy AI-powered applications and data tools for front-office teams. The role sits in a central Data & AI team, integrating large-scale data, machine learning models and modern software engineering practices in a fast-paced hedge fund environment.