AI & ML Engineer enhancing energy management software solutions at GreenPocket GmbH. Focusing on modern LLM architectures and AI integration for innovative user experience.
About the role
- Senior Machine Learning Engineer at Kraken utilities focusing on scalable ML-powered products in the energy sector. Collaborating with cross-functional teams to solve customer-centric challenges.
Responsibilities
- Design, build and deploy machine-learning and AI-powered systems that solve real business and customer problems
- Work end-to-end: from data exploration and experimentation through to production deployment, monitoring and iteration
- Collaborate closely with product managers and engineers to shape solutions that are practical, scalable and maintainable
- Lead deep technical investigations into complex or ambiguous problems, including critical bugs across multiple systems
- Help define and improve ML and engineering best practices within the team
- Run and analyse experiments (e.g. A/B tests) to validate product and model improvements
- Stay up to date with advances in ML, GenAI and developer tooling, and apply them thoughtfully to our products
- Contribute to a culture of learning through knowledge sharing, internal talks and mentoring
Requirements
- Strong hands-on experience applying machine learning in production environments (industry or equivalent research experience) with a proven track record of writing maintainable, testable code in complex codebases.
- Excellent Python skills and solid SQL experience
- Deep understanding of ML fundamentals: data analysis, model selection, evaluation, deployment and monitoring
- Experience working with ML / data libraries such as pandas, NumPy, scikit-learn, PyTorch or TensorFlow
- Comfort working in a software-engineering-heavy environment (version control, CI/CD, code reviews, MLOps principles)
- Experience building and operating systems on cloud infrastructure (AWS preferred)
- Ability to clearly explain technical concepts and trade-offs to a wide range of stakeholders
- Confidence working autonomously, asking questions early, and collaborating across teams and with clients
- Nice-to-have: Experience building GenAI or NLP-based products
- Nice-to-have: Exposure to LLM tooling, prompting, agents or evaluation techniques
- Nice-to-have: Experience with Kubernetes, dbt, or modern data tooling
- Nice-to-have: Experience running production experiments (A/B testing)
- Nice-to-have: Experience mentoring junior colleagues and leading workstreams
Benefits
- Flexible working arrangements
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
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