Senior Machine Learning Engineer

October 23

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Gorilla - Decisions, based on data

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Hi there, we are Gorilla. We are a software scale-up shaping the future of energy retail. Our mission is to empower enterprises to unlock the power of their data, with data-driven pricing, forecasting and reporting solutions that streamline operations and lower risk.

11 - 50 employees

Founded 2018

📋 Description

• 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Flexible work options - whether you choose Office Mix or Remote First Mix (currently available within certain timezones and locations) • Country-specific mobility benefits • Ability to work flexible hours • Equipped with the best technology for remote work • Generous PTO allowance • Health insurance coverage • Career growth opportunities • International travel for company-wide gatherings