At a Glance
- Tasks: Join our team to build and deploy innovative machine learning models for climate impact.
- Company: Gigaton, a mission-driven tech company focused on reducing carbon emissions.
- Benefits: Equity options, flexible working hours, 30 days holiday, and a generous pension scheme.
- Other info: Collaborative environment with opportunities for growth and innovation.
- Why this job: Make a real difference in combating climate change while advancing your ML skills.
- Qualifications: 2+ years in machine learning, proficient in Python, and passionate about sustainability.
The predicted salary is between 50000 - 70000 £ per year.
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.
- 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.
Machine Learning Engineer employer: Gigaton
Gigaton is an exceptional employer, offering a dynamic work environment in London where innovation meets inclusivity. With a strong focus on employee growth, the company provides equity, flexible working arrangements, and an impressive 30 days of holiday, ensuring that team members can thrive both personally and professionally while contributing to cutting-edge AI solutions for industrial plants.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Gigaton.
✨Apply Directly through Our Website
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We think you need these skills to ace Machine Learning Engineer
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Gigaton, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Gigaton. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Gigaton
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Gigaton!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.