The One Planet strategy we are committed to here at Eneco sets an ambitious goal to be climate neutral by 2035. We want to achieve that goal for both us and our clients. To make it happen, we are dedicated to offering our customers innovative digital capabilities and smart solutions. Our team is working towards creating an exceptional online customer experience, through modernizing the Eneco chat, app and web environments. We are striving to deliver a superior digital customer experience that will stimulate and make it easier for our customers to become greener, every day.
As a Machine Learning Engineer in the GenAI Platform, you will play a key role in building platforms for GenAI products. Right now, we are looking specifically for someone who has experience in the intersection of machine learning and cloud infrastructure (Terraform) in Azure. You will work closely with platform owners, data scientists, and other machine learning engineers to develop, optimize, and deploy LLM-powered services that support Eneco’s consumers internally or externally.
Responsibilities- Designing pipelines that ingest, process, and interpret non-structured data.
- Designing, developing, and maintaining scalable GenAI components and tools used across the organization.
- Develop user interfaces or backend systems that interact with LLMs efficiently and safely.
- Collaborate with cross‑functional teams (product, engineering, data science) to bring AI-powered features to life.
- Design and implement RAG pipelines that combine LLMs with vector search (e.g. Azure AI Search).
- Monitor platform usage, cost, GenAI and/or LLM related metrics.
- Create evaluation framework for chatbot or GenAI related application.
- Infrastructure as Code: Terraform or similar tools.
- Experience working in a platform team / Ability to design systems that support multiple teams and use cases.
- Hands‑on experience with LLM APIs (OpenAI, Anthropic, Azure OpenAI) and open‑source models.
- Strong Programming Skills in Python and ML/AI toolkit like PyTorch, Hugging Face Transformers, LangChain, etc.
- Experience deploying ML/AI systems in a production environment.
- Experience using Docker, Kubernetes, or MLflow for model lifecycle management.
- Understanding of software engineering principles: testing, CI/CD, version control, containerization.
- Experience building AI-enabled applications, such as chatbots or intelligent agents.
- Experience with REST APIs, microservices, and scalable backend systems.
- Familiarity with prompt engineering, RAG, and model fine‑tuning techniques.
- Cloud Platforms: Production experience with cloud services (Azure).
- Can be more pragmatic and flexible with pro‑code, low‑code or no‑code solution.
- Experience in Machine Learning, NLP, or AI Engineering.
You will be working together with other Machine Learning Engineers and Data Scientists. Together, you will shape the GenAI platform so either Eneco internal employees or external consumers can benefit from the GenAI technology. Within the team, we encourage learning, actively seek out collaboration, celebrate successes, and learn from failures.
Please contact our recruiter at Venetia.dewit@eneco.com
Benefits- Drive Eneco’s climate‑neutral mission by 2035 through cutting‑edge GenAI solutions that make customers greener every day.
- Shape and scale Eneco’s next‑generation AI platform – where Machine Learning meets real‑world impact.
- Join a collaborative, forward‑thinking team that values innovation, learning, and building AI products that truly matter.
€60000 - €80000 monthly