Senior Machine Learning Engineer

Senior Machine Learning Engineer

Location

London, UK (Hybrid) or Remote from the UK

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 focuses on creating reliable AI systems that can support long‑running workflows, persistent context, multi‑step reasoning, external tool interaction, and real‑world task completion.

The goal is to help users complete everyday tasks significantly faster through intelligent automation.

The Role

As a Senior Machine Learning Engineer, you will be an independent owner of critical machine learning subsystems in production.

This is a hands‑on, high‑impact role where you will take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale.

The role is focused on technical depth, production quality, and delivering real user impact.

Key Responsibilities

• Build core ML systems that power a proactive, long‑horizon AI product.
• Own work end‑to‑end across data preparation, training, evaluation, inference, and iteration.
• Turn research ideas into production‑ready systems that operate reliably at scale.
• Debug model failures and system issues using real production signals.
• Ship improvements quickly, measure outcomes, refine, and repeat.
• Collaborate closely with research, product, and engineering teams to deliver real user impact.
• Mentor and review work from other ML engineers through example and strong technical judgement.
• Work within real production constraints including latency, cost, reliability, and safety.
• Technology Stack
• Python
• Py Torch
• JAX
• GPU‑based training and inference systems
• Ideal Experience
• Technical Skills
• Experience building and shipping machine learning systems used by real users.
• Strong understanding of how modern ML models behave — and fail — in production environments.
• Ability to write strong, production‑quality code.
• Systems‑thinking mindset, with the ability to design maintainable and scalable solutions.
• Personal Attributes
• Strong ownership mindset.
• Comfortable working independently and pushing work through to completion.
• Fast learner with clear communication skills.
• Bias toward iteration, measurement, and continuous improvement.
• Able to bring structure and judgement to ambiguous technical problems.
• Success Measures
• Ensure ML models and production systems consistently meet accuracy, latency, reliability, and efficiency targets.
• Monitor, debug, and resolve complex production issues with minimal disruption.
• Build robust, scalable, and maintainable training, inference, and data pipelines.
• Drive measurable improvements in ML systems using real‑world signals and user feedback.
• Provide mentorship and technical guidance to peers.
• Help raise the overall ML engineering standard across the team.
• Collaborate cross‑functionally to ensure ML features integrate smoothly into products and meet business goals.
• Working Environment

The company believes exceptional products are built by small, world‑class teams with high talent density.

The team is hands‑on, collaborative, and moves quickly while balancing high‑quality delivery with continuous learning.

Team members are expected to bring structure, exercise sound judgement, and execute independently while contributing to a product designed to deliver practical AI benefits at global scale.

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