Senior Machine Learning Engineer (Energy)

Location: Rotterdam, Netherlands; hybrid work with 40% in the office, 40% from home, and 20% flexible work. With manager approval, work abroad within approved countries for up to 3 weeks per year, with a maximum of 2 consecutive weeks.

Gross annual salary: €88,000–€131,000, including FlexBudget and an 8% holiday allowance; a bonus or collective profit sharing may apply depending on the role.

Company

hirify.global is accelerating the energy transition through renewable-energy initiatives and an ambition to become climate neutral by 2035.

What you will do

• Work with data scientists to experiment with and operationalize machine learning models for demand forecasting, asset detection, and market simulations.
• Design, build, and maintain backtesting, experimentation, data, and feature-engineering frameworks.
• Productionize, version, release, roll back, and optimize ML models in reliable, scalable pipelines.
• Implement validation, safeguards, monitoring, observability, drift detection, and anomaly monitoring for forecasting models.
• Handle incomplete, delayed, or partial data and resolve operational incidents through post-mortems.
• Set engineering standards, drive architectural decisions, document data lineage, and mentor engineers.

Requirements

• Over 5 years of experience and strong software engineering skills in Python.
• Proven experience productionizing, maintaining, and monitoring ML models and pipelines.
• Hands-on experience with Databricks or similar distributed data and compute platforms.
• Experience deploying workloads in containerized or service-based execution environments.
• Experience designing or maintaining backtesting and simulation frameworks.
• Strong understanding of reproducibility, validation, reliability, time-series or event-driven systems, and production-first engineering.

Nice to have

• Experience with demand forecasting, energy markets, asset detection, cloud-native architectures, or scalable distributed systems.
• Experience collaborating with data scientists and data engineers.
• Experience with dbt, Snowflake, and Java.

Culture & Benefits

• Highly technical, production-first environment focused on engineering quality, ownership, and operational reliability.
• FlexBudget can be paid out, used for additional holidays, or saved.
• Personal and professional development support.
• Hybrid flexibility across home, office, and approved work-abroad arrangements.

Hiring process

• Contact the recruiter to begin the application procedure.