Reinforcement Learning Engineer

Ocado Group
Hatfield
1 year ago
Applications closed

Related Jobs

View all jobs

Robotics / Computer Vision Engineer

Reinforcement Learning Engineer | Ocado Technology | Hatfield | Hybrid (2 days office) About us: Leading online retail into the future Ocado Technology is powering the future of online retail across the globe through disruptive innovation and automation. Join us to create world-leading systems at the intersection of robotics , cloud platforms, big data, machine learning, software development, and beyond. We're constantly reinventing ourselves, learning fast, evolving our craftsmanship and taking risks as we strive to fulfil our mission to change the way the world shops. We enable some of the world's most forward-thinking retailers to do grocery online profitably, scalably and sustainably. Over the past two decades, we have developed a wide technology estate that includes robotics, AI and machine learning, simulation, forecasting and edge intelligence which all form part of our game changing 'Ocado Smart Platform' product. We champion a value-led culture to get our teams working at their very best and to help create a collaborative working environment that our people love. Core values of Trust, Autonomy, Craftsmanship, Collaboration and Learn Fast help drive our innovative culture. About the role: We are looking for a Machine Learning Engineer in Reinforcement Learning who can play a key role in evolving our autonomous bot control systems through the development and deployment of novel algorithms. We operate over 10k bots worldwide - in 2022 they made over 15 billion individual moves and travelled a combined 72 million kilometres - being at a considerable scale for benefiting from potential efficiency gains. This is an opportunity for the right individual to make a significant and lasting impact in the way Ocado operates and thinks about its core technology product. You should think about applying if you're passionate about novel applications of bleeding edge machine learning in solving some of the biggest problems facing e-retailers the world over. Your background might be academia or equivalent practical experience applying Reinforcement Learning in industry. The role will be embedded in a cross functional team of highly motivated experts in Ocado's technology, simulation, software engineering, and ML, working together to apply the cutting edge in ML to high impact industrial applications at scale. The right individual will be a thought leader within the team, and also seek to use their expertise to contribute to and influence the wider data science community across the entire technology business. Roles and responsibilities will include: Designing, implementing and evaluating applications of cutting edge machine learning, such as Reinforcement Learning, to control industrial systems at scale Collaborating with a range of teams and stakeholders to ensure projects are properly scoped, planned and executed, so there is successful utilisation of research outputs Keeping up to date with the latest advances in the field through following the literature and attending conferences Report and present findings and developments to technical and non-technical stakeholders What we're looking for: PhD in a technical field or equivalent practical experience. PhD in Reinforcement Learning would be an advantage Relevant experience to the position, such as working on applications of reinforcement learning in control systems Experience with the full life cycle of a data science project including delivering models into production and measuring the value delivered Someone who can collate successfully with a wide range of smart people with different perspectives and areas of expertise Someone who is curious, passionate about what they do, and highly self motivated This is an incredible opportunity to play a pivotal role in advancing our world leading automated solution and push the boundaries of what AI can do in retail fulfilment. What do I get in return: Hybrid working (2 days in the office ) 30 day work from anywhere policy Remote working for the month of August Wellbeing support through Apps such as Unmind and an Employee Assistance Programme 25 days annual leave, rising to 27 days after 5 years service (plus optional holiday purchase) Pension scheme (various options available including employer contribution matching up to 7%) Private Medical Insurance 22 weeks paid maternity leave and 6 weeks paid paternity leave (once relevant service requirements complete) Train Ticket loan (interest-free) Cycle to Work Scheme Opportunity to participate in Share save and Buy as You Earn share schemes 15% discount on Ocado.com and free delivery for all employees Income Protection (can be up to 50% of salary for 3 years) and Life Assurance (3 x annual salary) Share options LI-JT1 LI-OT LI-HYBRID

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.

The Skills Gap in Machine Learning Jobs: What Universities Aren’t Teaching

Machine learning has moved from academic research into the core of modern business. From recommendation engines and fraud detection to medical imaging, autonomous systems and language models, machine learning now underpins many of the UK’s most critical technologies. Universities have responded quickly. Machine learning modules are now standard in computer science degrees, specialist MSc programmes have proliferated, and online courses promise to fast-track careers in the field. And yet, despite this growth in education, UK employers consistently report the same problem: Many candidates with machine learning qualifications are not job-ready. Roles remain open for months. Interview processes filter out large numbers of applicants. Graduates with strong theoretical knowledge struggle when faced with practical tasks. The issue is not intelligence or effort. It is a persistent skills gap between university-level machine learning education and real-world machine learning jobs. This article explores that gap in depth: what universities teach well, what they routinely miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in machine learning.