ML Platform Engineer (AI)

Location: United Kingdom; hybrid role based in London, Greater London

Company

Builds proactive AI-native applications for conversations, errands, organisation, and workflows, with a focus on reliable long-running tasks, persistent context, and real-world completion.

What you will do

• Build and operate ML infrastructure and platforms powering AI products.
• Design systems for model training, evaluation, deployment, inference, experimentation, and continuous improvement.
• Optimise model-serving and inference infrastructure for high-throughput and low-latency workloads.
• Develop reliable data preparation, training, evaluation, model release, and ML workflow pipelines.
• Build evaluation, benchmarking, observability, monitoring, tracing, and alerting infrastructure for AI/ML workloads.
• Collaborate with AI engineers, researchers, and product engineers to deliver production-ready infrastructure and reusable platform primitives.

Requirements

• Strong software engineering fundamentals and experience building production systems.
• Experience building ML infrastructure, platforms, or production machine learning systems.
• Experience with model deployment, inference, evaluation, or data pipelines.
• Strong understanding of distributed systems and system reliability.
• Production-quality coding skills and a focus on ownership, experimentation, and continuous improvement.
• Experience with Python, PyTorch or JAX, cloud infrastructure, distributed systems, ML pipelines, GPU infrastructure, vector databases, and retrieval infrastructure.

Culture & Benefits

• Hybrid work arrangement in London, United Kingdom.
• Fast-moving environment with ambiguous technical problems and a strong ownership mindset.
• Focus on experimentation, continuous improvement, and rapidly evolving AI models and inference techniques.