Machine Learning Engineer

Planet A Ventures; Greater London; On-site; GBP 70,000 - 90,000; Full time

Benefits offered by this job

Equity in the company

Flexible working

30 days of holiday

Generous pension scheme

Job summary

Gigaton is seeking a Senior Machine Learning Engineer to develop models that drive our innovative AI solutions aimed at reducing carbon emissions. You will play a crucial role in a collaborative environment, contributing to both engineering and research efforts in machine learning.

Your responsibilities include building machine learning models, collaborating with product teams, and establishing best practices. A passion for climate change mitigation and expertise in Python and machine learning techniques are essential.

Qualifications

• 2+ years of experience as a machine learning engineer.
• Familiar with several ML techniques and theoretical knowledge.
• Experience working in a scientific environment.

Responsibilities

• Build, test, and deploy machine learning models.
• Contribute to technical innovation across the machine learning lifecycle.
• Collaborate with the product team on customer projects.

Skills

Machine Learning techniques

Python

Time-series modelling

Cloud compute infrastructure

Data optimization

Education

Degree in machine learning, physics, or chemistry

Tools

scikit-learn

PyTorch

AWS

GCP

Azure

Job description

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 applying cutting‑edge AI where it matters most. We’re a small and growing team of scientists, engineers, and strategic thinkers who care deeply about impact and believe in getting there with good humour and urgency. Our SaaS products help heavy industry optimise operations in real time, cutting costs and carbon today while building the foundation for the next industrial revolution.

We are seeking a Senior Machine Learning Engineer to help build the models that underpin these control systems and help us level up our machine learning infrastructure.

We don’t draw a specific line between engineering and research 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

• Work in the machine learning team as an individual contributor, building, testing and deploying our models.
• Contribute to technical innovation and problem‑solving across the machine learning lifecycle.
• Collaborate with the product team on customer projects, planning, designing and delivering the work packages required, as well as playing a significant role in the development of our wider 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 several 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 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 prior experience with time‑series modelling and industrial or IoT data.
• You have experience in any of: dynamical systems, 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 or chemistry.
• 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.

Benefits

• 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.