Top Tech Jobs & Startup Jobs in London

Build and maintain scalable ML infrastructure for LLM post-training, RL, evaluation, inference, and agentic workflows. Design data-control systems, optimize training and inference performance across networking, storage, and compute, and deliver tooling for experiments, evals, dashboards, reproducibility, and failure inspection. Collaborate with researchers and product to iterate models and infrastructure.

Train, fine-tune, and deploy large-scale multimodal models (vision, video, audio, speech). Build multimodal data pipelines, run experiments, optimize MoE and inference (quantization, distillation, low-latency), and develop multimodal alignment/RLHF pipelines. Define evaluation benchmarks and ship models to production.

Build and automate GTM systems to acquire and retain customers: own CRM, design GTM data model, create pipelines, deploy AI agents, build integrations and enrichment workflows, and iterate on outbound/inbound playbooks to generate qualified pipeline.

Train and post-train LLMs using SFT/RLHF/DPO, build reward models and large-scale data pipelines, run distributed multi-GPU training, design evaluation benchmarks, and optimize models for production inference and serving.

Own the full enterprise sales cycle for an AI safety platform: prospect, qualify, demo, negotiate with technical and executive stakeholders, close net-new deals, provide feedback to product, and help build repeatable sales processes and playbooks.

Design and run adversarial single- and multi-agent environments to find concrete failure modes in LLM agents. Orchestrate large-scale experiments against external APIs and internal models, instrument emergent behaviors, catalogue failures, and translate findings into internal models and public research.

Build, own, and maintain internal benchmark suites for single- and multi-turn content and agentic guardrails; create benchmarks distinguishing model capabilities; extend evals to new verticals and product features; collaborate on research quantifying realistic LLM and agent failure modes; support product integration of core model functionality.

Full-cycle recruiter for an AI safety startup, sourcing and hiring engineering, AI research, product, and business roles across the US and Europe. Build technical pipelines, conduct structured interviews, assess candidates for technical and cultural fit, improve recruiting processes and tooling, and advise hiring managers and leadership.

Build and maintain end-to-end automated test frameworks for web and API platforms, integrate tests into CI/CD, own test coverage, write bug reports, and improve test reliability and speed.

Design, build, and own backend services in Rust for real-time policy checks at scale. Ship end-to-end features from API design to deployment, optimize performance and reliability, collaborate with product and ML teams, and improve observability and throughput for high-volume APIs and data pipelines.