Machine Learning Engineer

Location: Commutable distance for either Bristol or London offices

Salary: competitive salary and excellent benefits.

Fathom is a leading water intelligence company leveraging cutting-edge machine learning to transform how we understand and manage water systems. We develop ML approaches such as diffusion, pixelwise regression, sensor fusion and GNNs to create DEMs, regionalise our data, predict riverflow and downscale climate data. As we expand our in-house ML capabilities, we're looking for a talented and enthusiastic Machine Learning Engineer to join our growing team.

This is a unique opportunity to work across diverse and impactful projects, collaborating closely with domain experts to build robust, data-driven solutions from the ground up. We are committed to developing novel methods, implementing state-of-the-art research, and contributing to the scientific community through peer-reviewed publications. We don't just prompt-engineer or build brittle agents; we focus on crafting rich datasets and training models from scratch, deeply integrating with our scientific understanding.

What you'll do:

• Implement and develop machine learning models: Work on a variety of projects, translating research papers into practical ML solutions or building and developing models from first principles.
• Contribute to diverse projects: Get involved in areas such as computer vision for DEMs, diffusion models for climate downscaling, and neural networks for hydrological predictions.
• Collaborate with domain experts: Partner with our scientists and hydrologists to understand complex problems and develop effective ML solutions.
• Work with spatial data: Utilize and process various geospatial data types, contributing to our advanced spatial analytics.
• Support MLOps and infrastructure: Aid in the maintenance and deployment of ML models, ensuring robust and scalable solutions.
• Promote best practices: Help foster a culture of industry-standard coding practices, including effective use of Git/GitHub and project management tools like ClickUp.
  
  

We're looking for someone with:

• A strong foundation in machine learning principles and techniques.
• Candidates with 1-2 year industry experience and ideally a relevant PhD
• Proficiency in Python and relevant ML libraries (e.g., PyTorch, TensorFlow, scikit-learn).
• Experience or a keen interest in working with spatial data types and geospatial libraries (e.g. geopandas, xarray).
• A pragmatic approach to numerical problem-solving, ideally demonstrated through academic or project work.
• Familiarity with software development best practices, including version control (Git/GitHub).
• Experience with or a willingness to learn project management tools (e.g., ClickUp).
• Excellent problem-solving skills and a proactive, inquisitive mindset.
• Strong communication skills and the ability to work effectively in a collaborative environment.
  
  

Bonus points if you have:

• A background in physics, mathematics, or a related quantitative field.
• Experience with large-scale datasets and distributed computing.
• An understanding of hydrological processes or climate science.
• A portfolio of personal ML projects or open-source contributions.
  
  

Join Fathom and help us unlock the power of water intelligence through cutting-edge machine learning. If you're passionate about applying ML to real-world environmental challenges and eager to grow your skills in a dynamic, research-driven environment, we'd love to hear from you.
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