At a Glance
- Tasks: Lead exciting Machine Learning projects and mentor junior team members.
- Company: Join National Grid, a leader in energy transition and innovation.
- Benefits: Competitive salary, bonus potential, flexible benefits, and a strong pension scheme.
- Other info: Diverse and inclusive workplace with excellent career development opportunities.
- Why this job: Make a real impact in the energy sector with cutting-edge technology.
- Qualifications: 7+ years in ML Engineering, strong Python and SQL skills required.
The predicted salary is between 80000 - 95000 £ per year.
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:
- Lead Machine Learning projects end-to-end.
- Develop platform tooling (e.g., internal conda library, CLI tool for project setup, and provisioning infrastructure) for the Data Science team.
- Work with data scientists to understand their data needs and put together data pipelines to ingest data.
- Work with data scientists to take data science model prototypes to production.
- Mentor and train junior team members.
- Work with internal IT teams (security, Cloud, Global Active Directory, Architecture, Networking, etc.) to advance the team’s projects.
- Enhance code deployment lifecycle.
- Improve model monitoring frameworks.
- Refine project operations documentation.
- Design, provision, and maintain the cloud infrastructure needed to support Data Engineering, Data Science, Machine Learning Engineers, and Machine Learning Operations.
- Write high-quality code that has high test coverage.
- 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.
Lead Machine Learning Engineer in London employer: National Grid
At National Grid, we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters innovation and collaboration. With competitive salaries, generous bonuses, and a robust pension scheme, we ensure our employees are well rewarded for their contributions. Our commitment to diversity and inclusion, along with flexible working arrangements, empowers our team members to thrive both personally and professionally in the heart of the UK's energy sector.
StudySmarter Expert Advice🤫
We think this is how you could land Lead Machine Learning Engineer in London
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at National Grid or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to National Grid.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like National Grid.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like National Grid that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Lead Machine Learning Engineer in London
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at National Grid.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at National Grid and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at National Grid
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If National Grid uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
