Role overview
Leobit (leobit.com) is a full cycle web and mobile application development provider for technology companies and startups primarily located in the US, Canada, Australia, the UK, and the EU. Our technology focus covers .NET, Angular, React, iOS, Android, Ruby, PHP and a comprehensive range of other technologies from Microsoft, Web, and Mobile Stacks.
We are looking for a Machine Learning Engineer (Python) to join our team.
About the client:
Over more than 20 years, the company delivers market-leading weather intelligence software that empowers our customers to confidently assess and manage the impact of weather on their markets. Our flagship product is used throughout the trading day on monitors across the majority of trading floors in North America and Europe.
They are at the forefront of applying cutting-edge machine learning technologies to forecast renewable power generation and energy demand (load). Their mission is to leverage data-driven innovation to accelerate and transform the renewable energy sector.
What you'll work on
- Design and deploy sophisticated ML models for predicting renewable energy output and forecasting demand patterns
- Work with large datasets covering weather conditions, power generation, and usage trends to enhance prediction precision and dependability
- Collaborate across data science, engineering, product, and meteorology teams to embed weather-related inputs into live forecasting pipelines
- Track and refine model accuracy on an ongoing basis, adapting to new information, shifting industry dynamics, and evolving business requirements
- Rigorously assess model outputs through diagnostic testing, error investigation, and bias evaluation to deliver quantifiable gains
- Present findings through intuitive visualizations and practical recommendations tailored for audiences with varying technical backgrounds
What we're looking for
- Four years of professional experience in software development (at least)
- Proven experience developing machine learning models (preferably in renewable energy, power markets, weather-driven forecasting, or related domains)
- Strong expertise in Python, including experience with TensorFlow and PyTorch, and large-scale geospatial/time-series datasets using xarray
- Good knowledge of Git
- Experience building scalable, reliable data science workflows with large datasets
- Strong understanding of ML best practices across the model lifecycle (data preparation, training, evaluation, deployment), with an emphasis on reproducibility and documentation
- Strong analytical and problem-solving skills, with attention to detail and a structured approach to debugging and improvement
- Ability to communicate complex results clearly using data visualization and analysis tools
- Strong problem-solving, communication, and collaboration skills
- Strong analytical skills
- Bachelor's or Master's degree in computer science (or similar technical field)
- Level of English: Upper-intermediate (at least)