Top Tech Jobs & Startup Jobs in London

Design and build distributed systems for large-scale AI training, focusing on performance, stability, monitoring, and debugging of infrastructure.

The AI Deployment Engineer will guide enterprise customers in deploying Generative AI applications, ensuring business value realization and managing project lifecycles from prototyping to production.

Partner with OpenAI research teams to define hiring priorities and execute strategic searches for top AI/ML researchers and technical scientists. Proactively source and cultivate talent across industry and academia, influence compensation and leveling, advise on candidate evaluation and closing, and collaborate with sourcing partners on complex, high-impact hires.

Lead and coordinate Technology Capital Builds across Real Estate, IT, Security and vendors to deliver networks, low-voltage, AV, access control, surveillance, and datacenter systems on scope, schedule, budget, and quality, and transition systems to operations.

Develop and optimize large-scale compute systems for AI workloads, improving infrastructure reliability and performance across various layers of the stack.

Develop software for Codex focusing on enterprise solutions, building APIs, integrating with identity systems, and collaborating with teams to ensure quality.

Design and maintain scalable systems, collaborate with cross-functional teams, and enhance internal tooling while focusing on reliability and performance in infrastructure.

Lead end-to-end technical delivery of AI/LLM deployments: translate business outcomes into technical plans, run cross-functional execution, embed with customers for adoption, manage dependencies and sequencing, measure ROI, and codify reusable solution patterns while partnering with Product and Research.

Build, operate, and automate large-scale GPU/compute infrastructure for ChatGPT. Design platforms for capacity planning, scheduling, fleet health, observability, incident response, and AI-powered operational tooling to improve reliability, utilization, and developer productivity across thousands of GPUs.

The role involves leading and growing a team focused on delivering production systems, influencing deployments, and enhancing team performance under pressure, while collaborating across Product, Research, and Sales.