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# Senior Machine Learning Engineer

- **Company:** Deliveroo
- **Location:** London, UK
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Python (Programming Language), Machine Learning, Circleci, Large Language Models, Generative AI, Kubernetes, Infrastructure Automation Frameworks, Production Code, Machine Learning Operations, Virtual Agents, Docker
- **Published:** August 15, 2026
- **Apply:** https://www.totaljobs.com/job/senior-machine-learning-engineer/deliveroo-job107845775

## About the Role

* Significant experience as an ML Engineer or Data Scientist, with a proven ability to write high-quality production code in Python.
 * Demonstrated ownership of productionising Generative AI workstreams or Agentic AI projects, including a deep understanding of LLMs, transformers, and fine-tuning.
 * Proven ability to deploy and manage models using modern infrastructure tools such as Docker, Kubernetes, and CircleCI.
 * Strong foundational knowledge of traditional ML and evaluation techniques, balanced with a bias for simplicity and measurable business impact.
 * A collaborative mindset with experience mentoring peers and a drive to solve complex, real-world problems at scale.

Nice to Have

 * Experience with evaluation harnesses and frameworks specifically designed for Generative AI.
 * Familiarity with observability, monitoring, and safety techniques for deployed GenAI systems.
 * Experience working with strongly typed languages, such as Go., If you're excited about making a real impact in a fast-moving marketplace and growing your career alongside ambitious, supportive teams, we'd love to hear from you!

## Description

You'll be joining the Care team. Care is an area with significant opportunity and real customer impact; you'll take ownership of existing models and help define strong ML foundations in spaces that are still evolving, from LLM-powered automation to customer compensation logic.

Here's what your day-to-day might look like:

 * Own the full ML lifecycle: Lead the design, development, and productionisation of machine learning models used in customer support and high-stakes decision systems.
 * Architect for reliability: Build robust monitoring, evaluation, and alerting frameworks to detect model underperformance, drift, or unexpected behaviour in real-time.
 * Collaborate on product strategy: Partner closely with Product Managers to turn ambiguous customer problems into robust, scalable ML solutions.
 * Drive technical excellence: Provide technical leadership in areas with unclear ownership, setting the gold standard for ML quality, reliability, and maintainability.
 * Bridge science and engineering: Work with data scientists and engineers across the global organisation to embed models into high-performance, scalable systems.


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