Machine Learning & Optimization Engineer

**Company Description** Vireco is building a smarter way to operate complex systems across legacy industries. Our software helps organizations optimize energy use and operational performance through an automated digital twin approach that improves control strategies and identifies the external factors driving system costs. Beginning with airports, Vireco enables facilities to move beyond fixed schedules and reactive operations by learning how systems behave, anticipating how they are likely to respond, and supporting better real\-time decisions within practical operating constraints. The company is also engaging across a wide range of legacy sectors as it builds a long\-term presence in large, resilient industries that remain largely underserved by AI. **Job Description** We are looking for an ML \& Optimization Engineer to help transform Vireco’s current machine learning and optimization pipeline into a more standardized, deployable, and complete product. This role sits at the intersection of machine learning, optimization, applied software engineering, and real\-world deployment. You will work across our internal digital twin pipeline and optimizer stack, helping bring together model training and tuning, data flow, deployment, and refresh processes into a system that can run reliably on\-site. The goal is to make our platform easier to configure, maintain, and replicate while contributing to real\-time optimizer decisions, constrained control logic, model evaluation, debugging, and testing across both offline simulation and live operation. **Qualifications** * Background in engineering, computer science, or a related field * Experience with Python in production or research\-to\-production environments * Experience training and evaluating machine learning models * Familiarity with graph\-based ML, surrogate models, or digital twin\-style pipelines * Experience with applied optimization, including constrained objectives, loss design, and control or scheduling problems * Experience deploying applications or ML services in Linux\-based environments * Strong software engineering habits, including modular design, version control, testing, and reproducible workflows * Strong debugging and problem\-solving ability in real\-world environments * Nice to have: experience with MPC, DRL, MLOps workflows, time\-series modelling, forecasting, simulation\-based ML, power systems, control systems, HVAC, BMS data, or BACnet * Eager to grow with a team in a high\-paced environment that is actively innovating and helping transform the industries that power the world.