Staff Machine Learning Engineer

Staff Machine Learning Engineer

Location: London, UK (Hybrid) OR Remote

Employment Type: Full-Time

Department: Engineering

About the Company

The company is building an AI-native smart assistant designed to help everyday users manage conversations, tasks, organisation, and workflows with minimal prompting. The product is focused on delivering reliable AI systems capable of long-running workflows, persistent context, multi-step reasoning, and real-world task completion. The goal is to help users complete everyday tasks significantly faster through intelligent automation.

The Role

As a Staff Machine Learning Engineer (Technical Lead, Machine Learning), you will own the execution layer of the company's AI platform. Working at the intersection of research, infrastructure, and product, you'll be responsible for turning research direction into reliable, scalable, production‑grade machine learning systems. You'll ensure models are trainable, deployable, observable, and perform‑able in real‑world environments.

Key Responsibilities

• Own end-to-end ML system execution across data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
• Fine‑tune and adapt models using advanced techniques such as LoRA, QLoRA, SFT, DPO, and distillation.
• Architect and operate scalable inference systems while balancing latency, cost, and reliability.
• Design and maintain data systems supporting both synthetic and real‑world training data.
• Build evaluation pipelines covering performance, safety, robustness, and bias.
• Own production deployment, including GPU optimisation, memory efficiency, latency reduction, and scaling strategies.
• Collaborate closely with application engineering teams to integrate ML systems into backend, mobile, and desktop products.
• Make pragmatic trade‑offs and deliver improvements rapidly based on real‑world usage.
• Work within production constraints including reliability, cost, latency, and safety.

Technology Stack

• Python
• PyTorch
• JAX
• GPU‑based training and inference systems

Ideal Experience

Technical Skills

• Experience building and deploying real machine learning systems used by customers.
• Strong understanding of large‑scale machine learning models and their failure modes.
• Ability to write robust, production‑grade code.
• Experience architecting scalable ML infrastructure and production systems.

Leadership & Personal Attributes

• Technical leadership experience within ML teams.
• Strong ownership mindset and accountability for outcomes.
• Self‑directed, pragmatic, and highly execution‑focused.
• Excellent communication and collaboration skills.
• Comfortable operating in fast‑moving, high‑trust environments.

Success Measures

• Translate research and modelling work into production‑ready ML solutions with measurable performance targets.
• Build stable, scalable, and maintainable ML pipelines, training systems, and inference infrastructure.
• Rapidly detect, investigate, and resolve production issues.
• Support and enable other ML engineers to deliver high‑impact work efficiently.
• Deliver measurable improvements in model performance, reliability, and user outcomes over time.
• Balance innovation with operational excellence and system reliability.

Working Environment

The company believes exceptional products are built by small, world‑class teams with high talent density. The culture values ownership, speed, collaboration, and continuous learning. Team members are expected to exercise judgement, execute independently, and contribute to building AI products capable of delivering meaningful impact at global scale.

Diversity & Inclusion

We encourage applicants from all backgrounds, so if there is anything we can do to make our recruitment processes better for you and to allow you to show your best self, let us know. We also understand that some people require extra time to complete assessments, require alternative application methods and can also benefit from having interview questions or a guide to the type of questions pre‑interview. We are open to any suggestions or requests that you may have and are always looking for creative ways to assess talent. Our commitment to you is that you should always feel safe and secure when you’re working with us.