Software Engineer

Axle Energy
London
11 months ago
Applications closed

Related Jobs

View all jobs

Software Engineer - Data Engineering

Software Engineer - Data Engineering

Data Engineer - DV Cleared

MLOps Engineer

Data Engineer - SC Cleared

Lead Data Engineer

Were hiring engineers who ship fast, build delightful products, and want to step into the arena in the fight against climate change.

The electricity grid is changing beyond recognition, and without deploying new software to orchestrate it, well be unable to decarbonise. At Axle, were building the infrastructure thatll underpin the decarbonised energy system. Our software crushes CO2 and energy costs. Our goal is insanely ambitious, and were building a team to match the scale of this challenge. Weve just raised a Seed round from world-leading investors including Accel (TechCrunch) and were growing fast.

We make the technology to move energy usage to times when electricity is cheap and green. Our software controls vehicle charging, heating systems, and home batteries. We use machine learning to figure out what energy people will need, and when theyll need it. We control tens of thousands of energy assets, and were growing quickly.

Axle is a unique startup. Were building in a legacy industry and moving gigawatt-hours of electrons in the real world, but we operate at lightning speed. We ship extraordinarily quickly, and were experts in electricity systems. Were backed by some of the best investors in the world, and were growing the team to meet customer demand.

Requirements

You can expect:

  • insane amounts of ownership
  • hard technical challenges
  • that what you build is commercially and environmentally valuable

In return, we ask for:

  • the courage to build new things fast
  • a commitment to real world impact over technical perfection
  • a desire to help build and lead an exceptional and tight knit team
  • deep-seated motivation to combat climate change

Interview process

  • Initial interview
  • Take-home exercise
  • Final interview (in-person)
  • Offer, references, and welcome to the team!

Tech stack

We like to build backends in Python, because it allows data scientists and engineers to collaborate closely and move quickly. We try a bunch of things in Figma before we build them in code, because its a fast and cheap way to get feedback. Everything we build lives in Docker, for minimal cross-platform faff and maximal reproducibility. We deploy on GCP but dont feel strongly about it.

Benefits

We love the idea of fully remote work but it doesnt work. For very early stage companies, people learn faster, get on better, and accomplish more when theyre spending a decent chunk of time together. We ask that you spend 2-3 days a week in our London office.

We areextremelykeen to build a diverse company, and were particularly eager to hear from candidates who dont fit the traditional role stereotypes. If youre motivated by our mission, please do reach out, even if you feel you might not ‘check all the boxes.

Seniority level

Mid-Senior level

Employment type

Full-time

Job function

Engineering and Information Technology

Industries

IT Services and IT Consulting

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.

Careers

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

Jobs

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.

Careers Jobs

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.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.