Technical Lead, Machine Learning (AI)

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

Company

Building proactive AI-native applications that help users manage conversations, errands, organization, and workflows with minimal prompting.

What you will do

• Own end-to-end ML systems across data, training, evaluation, inference, and deployment.
• Build and evolve training, fine-tuning, and high-quality real-world and synthetic data pipelines for large models.
• Design evaluation systems covering capability, robustness, safety, and real-world product performance.
• Architect and optimize GPU-based inference systems for latency, memory, utilization, cost, and reliability.
• Establish production infrastructure for model deployment, monitoring, debugging, and continuous improvement.
• Partner with research and application engineering to translate model capabilities into product improvements.

Requirements

• Experience building and shipping production ML systems used by real users.
• Strong understanding of large-model training, fine-tuning, evaluation, and inference.
• Strong software engineering and systems fundamentals, with production-grade coding practices.
• Experience operating ML workloads at meaningful scale, particularly GPU-based systems.
• Strong technical judgment, independent execution, and comfort navigating ambiguous problems.
• High standards for correctness, reliability, experimentation, measurement, and production quality.

Nice to have

• Experience understanding large-model failure modes and improving model reliability in production.

Culture & Benefits

• Small, hands-on, high-talent-density team with broad engineering ownership.
• Fast decision-making and close collaboration with limited process overhead.
• Engineers are expected to exercise strong judgment and execute independently.
• Interviews are conducted via virtual meetings and/or onsite, with a process of three to four interviews.
• Technical team members evaluate applications and aim to provide a prompt decision.