Freelance Machine Learning Engineer (3-6 months FTC)

Join us at Gorilla and be part of a mission to transform the energy industry. At Gorilla, you'll play a vital role in delivering cutting edge data solutions for a lower carbon future. We focus on providing efficient, reliable, and flexible SaaS solutions for data processing and analysis in the energy sector. Together, we're driving digital transformation, maximising ROI for clients, and contributing to achieving net zero emissions through technology and data driven insights.

The energy transition creates immense challenges and opportunities. Our Calculation Algorithms Team sits at the core of Gorilla's product, turning complex energy data into actionable insights. This team builds the intelligence that powers our customers' pricing, forecasting, and billing capabilities. It's where deep market expertise meets advanced engineering. As part of this group, you'll help design and deliver algorithms that run at scale, process millions of energy data points, and enable energy retailers to operate efficiently in volatile markets.

As a Freelance Machine Learning Engineer, you'll take ownership of the design, optimisation, and deployment of forecasting algorithms and ML based data solutions that power Gorilla's next generation platform. You'll lead projects focused on improving forecasting accuracy, developing production ready ML models, and enhancing the tooling and infrastructure that support model deployment and monitoring. This is a hands on, high impact role where you'll shape how Gorilla applies ML and AI to energy data within a 3-6 month engagement.

• Design, build, and maintain forecasting algorithms and ML models that deliver measurable improvements in performance and scalability.

• Develop and refine tooling and processes for the full ML model lifecycle, from training and validation to deployment and monitoring.

• Collaborate with Product, Data, and Engineering teams to integrate forecasting capabilities into production environments.

• Evaluate and apply advanced ML and deep learning techniques to enhance forecasting accuracy.

• Optimise model performance in distributed and cloud based environments such as AWS or Databricks.

• Document and share best practices for ML engineering, deployment, and version control.

• Mentor engineers and contribute to a culture of technical excellence through collaboration and learning.

• 5+ years of experience in software engineering and 5+ years in ML engineering, with proven delivery in production environments.

• Strong proficiency in Python and experience with the modern data stack such as SQL, Pandas, NumPy, SciPy, Dask, Polars, DuckDB, or PySpark.

• Deep understanding of time series forecasting, model evaluation, and statistical modelling.

• Experience with ML tooling, CI/CD pipelines, and cloud based platforms (AWS, Databricks).

• Exposure to deep learning and advanced techniques for forecasting.

• Strong communication skills and ability to collaborate effectively in a cross functional team.

• Technical leadership mindset with a focus on reliability, scalability, and best practices.

• 3-6 month contract, starting as soon as possible.

• Remote first setup; candidates must be based in Belgium, the UK, or Germany.

• Day rate based on experience and location.