ApplySarthi

Machine Learning Engineer

Gigaton

Tailor my CV for this job, freeView job and applyYour CV rewritten for this role, from your real experience. Sign in with Google, nothing to install.

Got this interview? Our apps help you get the job.

Skills named in this job

Read from the description itself, not inferred.

This role on the market

1,472 open learning roles across 349 companies are on ApplySarthi right now, most of them in Bengaluru (51), Hyderabad (31), Delhi NCR (9).

What learning roles keep asking for: Machine learning (63%), Python (53%), PyTorch (36%), LLMs (30%), Deep learning (26%), AWS (22%), C++ (19%), Generative AI (17%) — counted across their open postings here.

Machine Learning Engineer jobs in the United Kingdom · Machine Learning Engineer jobs in London · Remote Machine Learning Engineer jobs · AWS jobs · Azure jobs · Excel jobs · GCP jobs

Gigaton has 6 open roles listed here.

Counted across 14 company job boards, updated as roles open and close.

Preparing for this interview

Interviews for learning roles keep coming back to Machine learning, Python, PyTorch, LLMs. Practise those questions before you sit with Gigaton.

Questions you are likely to be asked

  1. Why do you want to join Gigaton?
  2. What is your experience with Machine learning? Tell me one thing you learned the hard way.
  3. What would you check first if a model's accuracy dropped after going live?
  4. When would you not use machine learning for a problem?
  5. Walk me through a model you built, from the data to how it was used.

Prep Sarthi gives you a free mock interview: an AI interviewer asks you questions like these out loud, from your own CV and this job, and shows your score and your weakest answer.

Practise the Machine Learning Engineer at Gigaton interview free →

At Gigaton, we’re on a mission to cut gigatonnes of carbon emissions from the world’s biggest emitting industries (like cement, steel and glass), by building autonomous AI control and optimisation systems that learn and leverage the physics of manufacturing. Our products run heavy industrial plants more efficiently, more stably, and with lower emissions in real time - laying the foundation for the next industrial revolution. We are a team of scientists, engineers, builders, and operators who love hard problems, have high standards, and want to make change happen in the physical world. We care about deep tech, but we care even more about whether it delivers cost and carbon impact in a live plant, with real people, under real constraints. With Gigaton, you’ll solve really tough problems in places few people ever get close to, and build something that actually helps the planet. Are you up for the challenge? We are seeking a Machine Learning Engineer (ranging from mid to principal) to help build the models that underpin these control systems and help us level up our machine learning infrastructure. Whether in research or deployment focussed teams, we operate as one cohesive unit, sharing tech stack, knowledge, and objectives. Our focus spans from fundamental ML research to commercial-grade software development, offering diverse learning and impact opportunities. Your main responsibilities Reporting to a Machine Learning Team Lead, you will: Build state-of-the art systems which combine edge control with active learning algorithms to continuously deliver impact and reduce CO2 emissions. Work in the machine learning team as an individual contributor, building, testing and deploying our models, optimisers and controllers. Contribute to technical innovation and problem-solving across the machine learning lifecycle. Collaborate with cross-functional teams on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our product. Help establish best practices to improve our internal processes. Contribute to the design and implementation of robust, maintainable and scalable machine learning systems. You will also contribute to our fear-free development process by building tooling that helps the team move faster and more sustainably. You will be supported by continuous builds, tests, a constructive review system, and a strong culture of improving engineering processes. What a great fit looks like You have 2 or more years of experience as a machine learning engineer. You are familiar with ML techniques, and have both theoretical ML knowledge and experience implementing different types of solutions. You are proficient in Python and have a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit-learn, PyTorch). You have experience working in end-to-end machine learning deployments. You have experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study. Are passionate about making a positive impact on climate change mitigation and possess a strong interest in our mission. You’ll excel if You have experience in any of: control systems, time-series modelling, reinforcement learning, system identification, optimisation or bayesian statistics. You are used to working in a fast-paced startup environment with an agile process. You have a degree in machine learning, physics, chemistry, engineering, mathematics or computer science. You have a track record of developing novel ML methods in relevant fields. You are hungry for responsibility, enthusiastic about taking on the design and development of solutions to difficult problems, and eager to drive the progress of new products. You have a solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience in working with AWS, GCP, Azure, or other vendors. You have have designed and built systems end to end with software architectural best practice. In return for your hard work, we’ll give you 📈 Equity in the company: When we win, you win. You’ll get share options, so you’re part of our journey from the inside. 🕰️ Flexible working We trust you to know how and when you work best and to work that out with your team. 🌴 30 days of holiday (plus bank holidays). Rest is productive. Take the time you need to recharge 🪙 A generous pension scheme. We’re planning for the future in more ways than one. Our Operating Principles ↗️ Go Gig or Go Home : High Bar, All In. What we do matters to humanity, to our customers and to each other. We hold ourselves to an extraordinarily high bar and bring the urgency this mission requires. 🏭 Concrete Honesty : Be honest. As concrete forms the foundation of our world, genuine honesty and transparency are the bedrock of our culture. 🦾 Autonomous Ownership : High agency, high ownership. We build systems that take control and make things better. We do the same: see it, own it, drive it. 😄 Cement it with Kindness & Fun : Have fun, be kind. We're here to extend Earth's life, but ours is still limited. We want to enjoy the ride. To see these in full, go to Gigaton’s Operating Principles Notion page. Find more English Speaking Jobs in United Kingdom on Arbeitnow

Match this job to your CV

ApplySarthi scores your CV against this role, shows the skills you are missing, and writes a tailored version for the application.

Check my match →

Similar open roles

Need answers during your interview? Try Live Sarthi.

Live Sarthi, an Interview Sarthi app, shows answer suggestions during the call.

Try Live Sarthi free →

A Windows app, from the same team as ApplySarthi.

Listed on arbeitnow · posted 2026-11-02. ApplySarthi collects openings and links to application pages; the role is advertised by Gigaton, not by us.