Machine Learning Engineer
Overview
Gigaton is seeking a Machine Learning Engineer, ranging from mid to principal level, to join the team in London, United Kingdom. The organization builds autonomous AI control and optimization systems designed to cut carbon emissions in heavy emitting industries such as cement, steel, and glass. The engineering team operates across fundamental machine learning research and commercial-grade software development to run industrial plants more efficiently and with lower emissions in real time. Visa sponsorship may be offered for suitable candidates.
Requirements
Applicants must have two or more years of experience as a machine learning engineer, along with theoretical machine learning knowledge and experience implementing various solutions. Candidates need to be proficient in Python with a solid understanding of the ecosystem of tools and libraries supporting machine learning development, such as scikit-learn and PyTorch. Additional necessary qualifications include experience working in end-to-end machine learning deployments and background in a scientific environment across disciplines like physics, chemistry, materials science, and engineering through previous roles or study. A strong passion for climate change mitigation and an interest in the organization's mission are required.
What you get
The position includes company equity through share options, flexible working arrangements, and thirty days of holiday plus bank holidays. Employees also receive access to a pension scheme.
Links in this posting
- 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.
- 😄 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.
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