Senior Machine Learning Engineer
Role details
Job location
Tech stack
Job description
As a Senior Machine Learning Engineer, you'll take ownership of the design, optimisation, and deployment of forecasting algorithms and ML-based data solutions that form the backbone of Gorilla's next-generation platform.
You'll lead Gorilla's efforts in machine learning for forecasting, establishing best practices for model design, evaluation, and deployment in production. Collaborating with teams across Data, Product, and Engineering, you'll ensure that forecasting models scale efficiently, integrate smoothly with our platform, and deliver reliable, explainable results to our customers.
This is a forecasting-focused role that combines hands-on ML engineering with technical leadership. You'll set up the processes, tooling, and infrastructure needed to build, release, and monitor machine learning models at scale, shaping Gorilla's approach to ML and AI in energy data., * Design, build, and maintain forecasting algorithms and ML models that power Gorilla's energy insights at scale.
- Lead the technical direction for forecasting, ensuring models are accurate, explainable, and production-ready.
- Develop and improve the processes and tooling that support the full lifecycle of ML models, from training and validation to deployment and monitoring.
- Collaborate with Product, Data, and Engineering teams to integrate forecasting capabilities into the Gorilla platform.
- Optimise model performance, reliability, and scalability in distributed and cloud-based environments.
- Establish and document best practices for ML development, testing, and release management.
- Evaluate and apply modern ML and deep learning techniques to continuously enhance forecasting accuracy.
- Mentor engineers in ML engineering concepts, model lifecycle management, and performance optimisation.
- Contribute to building a culture of technical excellence through knowledge sharing, documentation, and collaboration., Our flagship office is in Antwerp, and we also have an office in London and co-working spaces in Reading (UK), Austin (US), and Melbourne (ANZ). This is a Remote First role, giving you the freedom to choose where and how you work: from one of our offices (if you're nearby), from home, or a mix of both. Please note that you must be based in Belgium, the UK, or Germany, as we are not able to consider candidates living in other countries. Occasional travel is required to attend team meetings.
Requirements
Do you have experience in SciPy?, * 5+ years of experience in software engineering and 5+ years in ML engineering, with proven impact in production environments.
- Expertise in Python and the modern data stack such as SQL, Pandas, NumPy, SciPy, Dask, Polars, DuckDB, or PySpark.
- Strong ML engineering skills, including model development, deployment, versioning, monitoring, and integration into data pipelines.
- Experience building and maintaining ML tooling and CI/CD pipelines for model management.
- Deep understanding of time-series forecasting methods and statistical modelling.
- Hands-on experience with cloud-based and data environments such as AWS and Databricks.
- Exposure to deep learning and advanced statistical techniques for forecasting.
- Familiarity with SaaS or software product environments; experience in energy data or a strong motivation to learn it is a plus.
- Strong communication and collaboration skills, with the ability to mentor peers and guide cross-functional alignment.
- A technical leadership mindset that drives standards, documentation, and scalability in ML and forecasting practices.
