Machine Learning Engineer - Utilities
Description For Machine Learning Engineer - Utilities
Kraken is at the forefront of innovative global developments in energy, creating a smart, sustainable energy system. Their tech platform is licensed to support 55 million customer accounts globally, with an ambitious goal to serve 100 million by 2027. The company is expanding into other utility sectors through Kraken Utilities, which has already secured partnerships with major clients like Severn Trent, Leep, Portsmouth Water, and Cuckoo.
The Machine Learning Engineer role sits within the newly formed Kraken Utilities innovation team, focusing on cutting-edge applications of ML/Data/AI. You'll work on fascinating challenges like improving water efficiency through smart meter data analysis for leak detection and enhancing customer support using LLM agents.
The technology stack is robust and modern, utilizing Python, SQL, pandas, Numpy, AWS, PyTorch, TensorFlow, and NLP tools. The development environment embraces continuous delivery, using tools like Github, CircleCI, and Terraform Enterprise, with monitoring through Datadog, Sentry, and Cloudwatch.
Working in a hybrid setting at the Oxford Circus office (2 days/week), you'll join a global engineering team of 1500+ professionals. The company culture emphasizes autonomy, quick learning, and impactful decision-making. Teams operate with flexibility, often using a Kanban-like approach, and engineers work in 'super teams' focused on key platform areas.
This is an excellent opportunity for a skilled Machine Learning Engineer to shape the future of utility management while working with cutting-edge technology in a rapidly growing, environmentally conscious company. The role offers the perfect blend of technical challenges, innovation, and the chance to make a real impact on sustainability and customer experience in the utilities sector.
Responsibilities For Machine Learning Engineer - Utilities
- Design, build, and deploy cutting-edge machine learning systems
- Work collaboratively with cross-functional teams
- Stay at the forefront of technology and evaluate new technologies
- Conduct A/B experiments and analyze results
- Adapt to changing responsibilities and focus areas as the company scales
Requirements For Machine Learning Engineer - Utilities
- 4+ years of hands-on experience applying machine learning to real-world business challenges
- Solid foundation in machine learning fundamentals
- Expertise in Python, SQL, ML/DL libraries (pandas, numpy, scikit-learn, tensorflow, pytorch, huggingface, matplotlib)
- Experience with cloud technologies, preferably AWS
- Strong communication skills
- Proficiency in software engineering fundamentals including version control and CI/CD pipelines
Benefits For Machine Learning Engineer - Utilities
- Flexible work arrangements
- Hybrid working model (2 days in office)
- Comprehensive benefits package
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