Machine Learning Engineer
Description For Machine Learning Engineer
Kraken, a part of Octopus Energy Group, is seeking a Machine Learning Engineer to join their global ML/AI team. This role is at the forefront of leveraging cutting-edge language modeling technology to enhance customer service in the energy sector.
As a Machine Learning Engineer, you'll be instrumental in bringing the next generation of AI-powered features to Kraken's platform. Your work will span the entire product lifecycle, from identifying innovative uses of new technologies to implementing and monitoring their performance in collaboration with front-end and back-end engineers.
The ideal candidate is passionate about the energy transition, self-driven, and quick to learn. You should have hands-on experience with LLMs in production environments, a strong background in machine learning, and an engineering mindset. Proficiency in Python, ML libraries, NLP, Kubernetes, and SQL is essential.
Kraken operates on a modern cloud data platform using AWS, Databricks, Delta Lake, dbt, Spark, and various other cutting-edge technologies. This role offers an exciting opportunity to work with state-of-the-art LLMs and prompting techniques, train in-house models, and stay at the forefront of AI advancements in the energy industry.
Join Kraken and help shape a more sustainable future by applying your ML expertise to optimize renewable generation, create a more intelligent grid, and enable utilities to provide exceptional customer experiences. If you're ready to make a big green dent in the universe through technology, this could be the perfect role for you!
Responsibilities For Machine Learning Engineer
- Identify uses of new technologies via exploration
- Work closely with operations teams to validate ideas
- Implement features in collaboration with front and backend engineers
- Create systems to monitor ongoing performance
- Use state of the art LLMs and prompting techniques
- Train models in-house where appropriate
- Stay up to date with changes in the field
- Deploy models via API using Python and Kubernetes
- Use MLflow to manage trained models
Requirements For Machine Learning Engineer
- Passionate about working in energy and contributing to the energy transition
- Curious and self-driven
- Learns fast and enthusiastic about learning new technologies
- Passion for LLMs and hands-on experience with using them in production
- Experience with machine learning and deploying models in production
- Engineering mindset with experience in Python, ML python packages, NLP, Kubernetes, SQL
