Be at the heart of actionFly remote-controlled drones into enemy territory to gather vital information.

Apply Now

Lead Machine Learning Engineer

National Grid
London
5 months ago
Applications closed

Related Jobs

View all jobs

Lead Machine Learning Engineer Graph ML

Contract Lead Machine Learning Engineer

Lead Machine Learning Research Engineer, Applied AI

Machine Learning Operations Lead

Machine Learning & AI Engineer

Machine Learning & AI Engineer

Lead Machine Learning Engineer
Date: Jan 9, 2025

Location: London, GB, WC2N 5EH

Company: National Grid

About The Role
At National Grid, we keep people connected and society moving. But it’s so much more than that. National Grid supplies us with the environment to make it happen. As we generate momentum in the energy transition for all, we don’t plan on leaving any of our customers in the dark. So, join us as a Lead Machine Learning Engineer, and find your superpower.

National Grid is hiring a Lead Machine Learning Engineer for our IT & Digital department. This is a hybrid role based in London.

Key Accountabilities

  1. Lead Machine Learning projects end-to-end.
  2. Develop platform tooling (e.g., internal conda library, CLI tool for project setup, and provisioning infrastructure) for the Data Science team.
  3. Work with data scientists to understand their data needs and put together data pipelines to ingest data.
  4. Work with data scientists to take data science model prototypes to production.
  5. Mentor and train junior team members.
  6. Work with internal IT teams (security, Cloud, Global Active Directory, Architecture, Networking, etc.) to advance the team’s projects.
  7. Enhance code deployment lifecycle.
  8. Improve model monitoring frameworks.
  9. Refine project operations documentation.
  10. Design, provision, and maintain the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations.
  11. Write high-quality code that has high test coverage.
  12. Participate in code reviews to help improve code quality.


Technologies/Tools we use:Python, Azure (Virtual Machines, Azure Web Apps, Cloud Storage, Azure ML), Anaconda packages, Git, GitHub, GitHub Actions, Terraform, SQL, Artifactory, Airflow, Docker, Kubernetes, Linux/Windows VMs.

About You
At least 7 years of hands-on industry experience in some combination of Software Engineering, ML Engineering, Data Science, DevOps, and Cloud Infrastructure work.
Expertise in Python which includes experience in libraries such as Pandas, scikit-learn. High proficiency in SQL.
Knowledge of best practices in software engineering is necessary.
At least 5 years of hands-on industry experience in some combination of the following technologies: Python ecosystem, Azure (VMs, Web Apps, Managed Databases), GitHub Actions, Terraform, Packer, Airflow, Docker, Kubernetes, Linux/Windows VM administration, Shell scripting (primary Bash but PowerShell as well).
A solid understanding of modern security and networking principles and standards.
A foundational knowledge of Data Science is strongly preferred.
Bachelor’s or higher degree in Computer Science, Data Science, and/or related quantitative degree is preferred from an accredited institution.

More Information
A salary between £80,000 – £95,000 – dependent on capability.

As well as your base salary, you will receive a bonus of up to 15% of your salary for stretch performance and a competitive contributory pension scheme where we will double match your contribution to a maximum company contribution of 12%. You will also have access to a number of flexible benefits such as a share incentive plan, salary sacrifice car and technology schemes, support via employee assistance lines and matched charity giving to name a few.

At National Grid, we work towards the highest standards in everything we do, including how we support, value and develop our people. Our aim is to encourage and support employees to thrive and be the best they can be. We celebrate the difference people can bring into our organisation, and welcome and encourage applicants with diverse experiences and backgrounds, and offer flexible and tailored support, at home and in the office.

Our goal is to drive, develop and operate our business in a way that results in a more inclusive culture. All employment is decided on the basis of qualifications, the innovation from diverse teams & perspectives and business need. We are committed to building a workforce so we can represent the communities we serve and have a working environment in which each individual feels valued, respected, fairly treated, and able to reach their full potential.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.

Why Machine Learning Careers in the UK Are Becoming More Multidisciplinary

Machine learning (ML) has moved from research labs into mainstream UK businesses. From healthcare diagnostics to fraud detection, autonomous vehicles to recommendation engines, ML underpins critical services and consumer experiences. But the skillset required of today’s machine learning professionals is no longer purely technical. Employers increasingly seek multidisciplinary expertise: not only coding, algorithms & statistics, but also knowledge of law, ethics, psychology, linguistics & design. This article explores why UK machine learning careers are becoming more multidisciplinary, how these fields intersect with ML roles, and what both job-seekers & employers need to understand to succeed in a rapidly changing landscape.

Machine Learning Team Structures Explained: Who Does What in a Modern Machine Learning Department

Machine learning is now central to many advanced data-driven products and services across the UK. Whether you work in finance, healthcare, retail, autonomous vehicles, recommendation systems, robotics, or consumer applications, there’s a need for dedicated machine learning teams that can deliver models into production, maintain them, keep them secure, efficient, fair, and aligned with business objectives. If you’re hiring for or applying to ML roles via MachineLearningJobs.co.uk, this article will help you understand what roles are typically present in a mature machine learning department, how they collaborate through project lifecycles, what skills and qualifications UK employers look for, what the career paths and salaries are, current trends and challenges, and how to build an effective ML team.

Why the UK Could Be the World’s Next Machine Learning Jobs Hub

Machine learning (ML) is becoming essential to industries across the globe—from finance and healthcare to retail, logistics, defence, and the public sector. Its ability to uncover patterns in data, make predictions, drive automation, and increase operational efficiency has made it one of the most in-demand skill sets in the technology world. In the UK, machine learning roles—from engineers to researchers, product managers to analysts—are increasingly central to innovation. Universities are expanding ML programmes, enterprises are scaling ML deployments, and startups are offering applied ML solutions. All signs point toward a surging need for professionals skilled in modelling, algorithms, data pipelines, and AI systems. This article explores why the United Kingdom is exceptionally well positioned to become a global machine learning jobs hub. It examines the current landscape, strengths, career paths, sector-specific demand, challenges, and what must happen for this vision to become reality.