Machine Learning Engineer
Job description
Machine Learning Engineer (mid to principal) at Gigaton, building the models, optimisers and controllers behind autonomous AI control and optimisation systems for heavy industrial plants such as cement, steel and glass.
At a glance
- Employment
- Full-time
- Work mode
- Remote · United Kingdom
What you'll do
- 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 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, and play a significant role in the development of the product
- Help establish best practices to improve internal processes
- Contribute to the design and implementation of robust, maintainable and scalable machine learning systems
- Build tooling that helps the team move faster and more sustainably within the fear-free development process
What we're looking for
- 2 or more years of experience as a machine learning engineer
- Familiar with ML techniques, with both theoretical ML knowledge and experience implementing different types of solutions
- Proficient in Python and a good understanding of the ecosystem of tools and libraries that support ML development (e.g., scikit-learn, PyTorch)
- Experience working in end-to-end machine learning deployments
- Experience working in a scientific environment across disciplines (particularly physics, chemistry, materials science, and engineering), either through previous roles or study
- Passionate about making a positive impact on climate change mitigation and a strong interest in the mission
Nice to have
- Experience in any of: control systems, time-series modelling, reinforcement learning, system identification, optimisation or bayesian statistics
- Used to working in a fast-paced startup environment with an agile process
- A degree in machine learning, physics, chemistry, engineering, mathematics or computer science
- A track record of developing novel ML methods in relevant fields
- 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
- A solid understanding of modern cloud compute infrastructure as it relates to machine learning, and experience working with AWS, GCP, Azure, or other vendors
- Designed and built systems end to end with software architectural best practice
Your team
Machine Learning team
Research and deployment focussed teams operating as one cohesive unit, sharing tech stack, knowledge and objectives; focus spans from fundamental ML research to commercial-grade software development.
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About Gigaton
Gigaton builds autonomous AI control and optimisation systems that run heavy industrial plants more efficiently, more stably, and with lower emissions in real time. The team is made up of scientists, engineers, builders and operators who care about deep tech delivering cost and carbon impact in a live plant.
Mission
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.
Key facts
- Products run heavy industrial plants more efficiently, more stably, and with lower emissions in real time
- Team of scientists, engineers, builders, and operators
- Focus spans from fundamental ML research to commercial-grade software development
What they value
- Go Gig or Go Home: High Bar, All In
- Concrete Honesty: Be honest
- Autonomous Ownership: High agency, high ownership
- Cement it with Kindness & Fun: Have fun, be kind