Principal MLOps, Marousi, Hybrid (2-3)

Our client is a global software company operating in the renewable energy sector, delivering software platforms for utility-scale solar, wind, and battery storage operators across multiple international markets. The role exists due to continued investment in the company’s battery storage analytics capabilities and the scaling of its production machine-learning infrastructure.

The Role

You’ll contribute to the design and operation of the production machine-learning pipeline that powers battery energy storage analytics across the platform. You’ll work across feature engineering, training infrastructure, experiment tracking, deployment, observability, and retraining workflows while collaborating closely with data science and platform engineering teams.

Within your first six months, you’ll be expected to contribute to the reliability and scalability of the ML production lifecycle, improve monitoring and drift-detection capabilities, and help establish reusable deployment patterns that accelerate the delivery of new analytical models into production.

What You’ll Bring

• 6+ years of experience building and operating production machine-learning pipelines at scale
• Strong Python engineering skills together with production experience in at least one systems language such as Go, Java, or C#
• Hands-on experience with modern ML and data platforms, including Databricks, MLflow, workflow orchestration, and model registry tooling
• Strong Kubernetes expertise, including Helm and GitOps tooling such as ArgoCD
• Production experience with Apache Kafka and stream-processing architectures
• Demonstrable experience managing real-world ML operational challenges including drift, regression, and infrastructure cost optimisation
• Fluency with AI-assisted engineering and agentic coding workflows
• Strong collaboration and communication skills in English

Nice to Have

• Open-source contributions within the MLOps ecosystem
• Experience working with industrial, telemetry, or IoT datasets at high event throughput
• Cost-engineering experience on cloud-native data and ML platforms

What’s in it for You

The role offers a salary commensurate with experience (€5000 - €6500) and the opportunity to work on cutting-edge battery storage analytics and renewable energy technologies. It follows a hybrid working arrangement, with two days onsite and three days remote each week in Athens, and provides a collaborative international environment that brings together applied science, machine learning engineering, and renewable energy technology. Additional benefits include a monthly meal allowance, private health insurance, and an annual bonus.