Head of Software Development - Machine Learning Engineering

Tesco Partners
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Data Science Manager

Senior Data Science Manager

Data Scientist – GenAI & AI Engineering

Machine Learning Engineer

Senior/Lead Machine Learning Scientist (Hands On)- International Consumer Bank

Machine Learning Engineer

About the role

At Tesco, we believe in the power of spending more time together, face to face, than apart. So, during your working week, you can expect to spend 60% of your time in one of our office locations or local sites and the rest remotely. We also recognise that life looks a little different for each of us. Some people are at the start of their careers, some want the freedom to do the things they love. Others are going through life-changing moments like becoming a carer, nearing retirement, adapting to parenthood, or something else. That’s why at Tesco, we always welcome a conversation about flexible working. So, talk to us throughout your application about how we can support.

As a Head of Software Engineering for Machine Learning Engineering, you’ll be a significant contributor to the delivery of products in one of Tesco’s most strategic technology areas. You’ll work with other engineers, data scientists, product managers, systems engineers, and analytics professionals to help deliver valuable and innovative outcomes for our customers. You’ll work within and across our Engineering and Data Science teams, delivering scalable products that improve how we serve our customers and run our operations. As Head of Software Development at Tesco, you hold a senior engineering management role and are the first level at which you manage other managers.

About the Team:

Within Tesco Data & Analytics, we help our customers and the communities where we operate get the most value from data. We build and run Tesco’s data platforms, we architect and engineer data onto these platforms, provide capabilities and tools to the analytics community across Tesco, and develop data products at scale.

Our Data Science teams are involved in a broad range of projects, spanning across supply chain, logistics, store and online. These include projects in the areas of Operations Optimisations, Commercial Decision Support (e.g. Forecasting and Range Optimisation), Online (e.g. Search and Recommendation) and Intelligent Edge (e.g. Computer Vision). Our Machine Learning Engineers work alongside our data scientists, helping with everything from development of tools and platforms, code optimisations through to deployment of solutions on the edge, cloud and big-data environments.

You will be responsible for
  • Accountability for delivering impact across teams within a directorate, as well as for effecting and leading change across the wider Technology organisation.
  • Responsibility to lead your team with a clear sense of purpose & vision.
  • Working with Data Scientists, Engineers, and Product teams across the software lifecycle.
  • Hire, retain, and engage engineering managers and senior engineering talent.
  • Promoting a culture of inclusion, autonomy, mastery, and delivery through directing, mentoring, coaching, and facilitation aligned to the broader technology organisation and Tesco values.
  • Ensure all colleagues are supported in their careers, with personal/professional development objectives and through continuous feedback and training.
  • Developing an environment that enables your teams to succeed in delivering and operating quality software, empowering teams to own technical decisions.
  • Sharing knowledge with the wider engineering community.
  • Building an effective execution process to ensure teams have awareness of overarching strategy, enabling them to be responsive during planning, development, and operational issues.
  • Working with key stakeholders to ensure teams deliver business value.
  • Acting decisively when required and being comfortable with managing ambiguity.
  • Driving continuous improvement of engineering practices, efficiency of development, and fostering innovation.
  • Empowering your team of engineers to own technical decisions whilst providing guidance and being responsible for best practices, striving to reduce waste, iterate quickly, and fail fast and forward.
  • Take responsibility to build industry-leading and extensible software in your area of ownership.
  • Lead and drive teams towards the right designs, architectural and programming principles, aligning to Tesco Technology’s agreed standards.
  • Evaluate the design and architectural decisions/choices of technical teams, advising on improvements to optimise systems and solutions.
  • Working with key stakeholders, ensuring teams deliver the right value.
  • Contributing to budget planning and forecasting for the Data Science domain.
You will need

An engineering background with strong knowledge of the Data Science Toolkit (Programming, Machine Learning, MLOps etc.) and bringing data science solutions into production.

Key Requirements Include:

  • Experience building and leading engineering teams within a Data Science setting.
  • A higher degree in engineering, computer science, maths, or science.
  • Customer focus with the right balance between outcome delivery and technical excellence.
  • The ability to apply technical skills and know-how to solving real-world business problems.
  • Demonstrable experience of building scalable and resilient systems.
  • Commercial experience contributing to the success of high-impact Data Science projects within complex organisations.
  • Awareness of emerging MLOps practices and tooling would be an advantage (e.g. feature stores and model lifecycle management).
  • An analytical mindset and the ability to tackle specific business problems.
  • Experience with different programming languages and a good grasp of at least one language. The ideal candidate is fluent in Python.
  • Use of version control (Git) and related software lifecycle tooling.
  • Understanding of common data structures and algorithms.
  • Experience working with open-source Data-Science environments.
  • Knowledge of open-source big-data technologies such as Apache Spark.
  • Experience building solutions that run in the cloud, ideally Azure.
  • Experience with software development methodologies including Scrum & Kanban.
  • A background or strong understanding of the retail sector, logistics, and/or e-commerce would be advantageous but is not required.
  • Practical experience with search technologies and recommender systems would be a plus.
What’s in it for you

We’re all about the little helps. That’s why we make sure our Tesco colleague benefits package takes care of you – both in and out of work.Click Hereto find out more!

  • Annual bonus scheme of up to 45% of base salary.
  • Car Cash Allowance.
  • Holiday starting at 25 days plus a personal day (plus Bank holidays).
  • Private medical insurance.
  • Retirement savings plan - save between 6% - 10% and Tesco will contribute 1.5 times this amount.
  • 26 weeks maternity and adoption leave (after 1 year’s service) at full pay, followed by 13 weeks of Statutory Maternity Pay or Statutory Adoption Pay. We also offer 4 weeks fully paid paternity leave.
About us

Our vision at Tesco is to become every customers favourite way to shop, whether they are at home or out on the move. Our core purpose is ‘Serving our customers, communities, and planet a little better every day’. Serving means more than a transactional relationship with our customers. It means acting as a responsible and sustainable business for all stakeholders, for the communities we are part of, and for the planet.

Diversity, equity, and inclusion (DE&I) at Tesco means that whoever you are and whatever your background, we always want you to feel represented and that you can be yourself at work. In short, we’re a place whereEveryone’s Welcome. We’re proud to have been accredited Disability Confident Leader and we’re committed to providing a fully inclusive and accessible recruitment process. For further information on the accessibility support we can offer, please clickhere.

We’re a big business and we can offer a range of diverse full-time & part-time working patterns across our many business areas, which means that we can find something that works for you. We work in a more blended pattern - combining office and remote working. Our offices will continue to be where we connect, collaborate, and innovate.

J-18808-Ljbffr

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.

AI Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Changing career into artificial intelligence in your 30s, 40s or 50s is no longer unusual in the UK. It is happening quietly every day across fintech, healthcare, retail, manufacturing, government & professional services. But it is also surrounded by hype, fear & misinformation. This article is a realistic, UK-specific guide for career switchers who want the truth about AI jobs: what roles genuinely exist, what skills employers actually hire for, how long retraining really takes & whether age is a barrier (spoiler: not in the way people think). If you are considering a move into AI but want facts rather than Silicon Valley fantasy, this is for you.

How to Write an AI Job Ad That Attracts the Right People

Artificial intelligence is now embedded across almost every sector of the UK economy. From fintech and healthcare to retail, defence and climate tech, organisations are competing for AI talent at an unprecedented pace. Yet despite the volume of AI job adverts online, many employers struggle to attract the right candidates. Roles are flooded with unsuitable applications, while highly capable AI professionals scroll past adverts that feel vague, inflated or disconnected from reality. In most cases, the issue isn’t a shortage of AI talent — it’s the quality of the job advert. Writing an effective AI job ad requires more care than traditional tech hiring. AI professionals are analytical, sceptical of hype and highly selective about where they apply. A poorly written advert doesn’t just fail to convert — it actively damages your credibility. This guide explains how to write an AI job ad that attracts the right people, filters out mismatches and positions your organisation as a serious employer in the AI space.

Maths for AI Jobs: The Only Topics You Actually Need (& How to Learn Them)

If you are a software engineer, data scientist or analyst looking to move into AI or you are a UK undergraduate or postgraduate in computer science, maths, engineering or a related subject applying for AI roles, the maths can feel like the biggest barrier. Job descriptions say “strong maths” or “solid fundamentals” but rarely spell out what that means day to day. The good news is you do not need a full maths degree worth of theory to start applying. For most UK roles like Machine Learning Engineer, AI Engineer, Data Scientist, Applied Scientist, NLP Engineer or Computer Vision Engineer, the maths you actually use again & again is concentrated in a handful of topics: Linear algebra essentials Probability & statistics for uncertainty & evaluation Calculus essentials for gradients & backprop Optimisation basics for training & tuning A small amount of discrete maths for practical reasoning This guide turns vague requirements into a clear checklist, a 6-week learning plan & portfolio projects that prove you can translate maths into working code.