Senior Optimization Engineer

Senior Optimization Engineer (MILP / Gurobi) 🚀Freelance role with a fast-growing energy tech company operating in the Nordic balancing markets. Mathematical optimization at the core of the product, not as a side feature. The challengeThousands of EV chargers, one optimization layer that turns their flexibility into MW committed to the grid every 15 minutes. You own the mathematical programs behind that: the offline training optimizer that computes historical capacity, and the real time bidding and activation solvers that decide what gets sold to the market. What you'll do 🎯Formulate and implement MILPs for EV fleet scheduling: charging logic, bid selection, capacity allocation, activation dispatchScale the training optimizer with decomposition (temporal, spatial, Lagrangian, column generation) to handle 180+ day lookbacks across 10,000+ chargersDesign bidding strategies for mFRR and FCR-D: turn capacity forecasts and price signals into revenue maximizing bids under uncertaintyModel EV charging physics: energy envelopes, power curves, semi continuous constraints, activation duration enduranceOwn the solver pipeline end to end, from formulation to CI/CD and scheduled executionConsume ML forecasts (disconnect probability, energy, price scenarios) as optimizer inputs, and define what the ML needs to produce Must have ✅4+ years formulating and solving constrained optimization problems (MILPs, LPs, stochastic programs) for scheduling, dispatch or resource allocationGurobi, Pyomo, CPLEX or OR-Tools at a level where you have tuned solver parameters, diagnosed infeasibilities and handled models with 100k+ variablesDecomposition techniques: temporal partitioning, Lagrangian relaxation, Benders, column generation or rolling horizonProduction quality Python, not notebooksExperience deploying and operating optimization workloads in production: CI/CD, job scheduling, monitoring, alerting when solves degradeAbility to turn physical constraints (power limits, energy conservation, time coupling) into formulations Nice to have ⭐Energy market mechanics: balancing, capacity markets, frequency regulation, demand responseEV charging, V2G, battery storage or DER aggregationNordic markets (SvK mFRR/FCR-D, Nord Pool)Stochastic or robust optimization under forecast uncertaintyDatabricks, PySpark, Delta LakeInfrastructure as code (Databricks Asset Bundles, Terraform) Why this projectLong term, full time, 100% remote. Your models control real MW on the Swedish grid every 15 minutes, and you define the bidding logic rather than implementing someone else's spec. Small team, no platform layer between you and production, plus a say in which markets and countries come next. If it fits, apply and we will review your profile 📩#Optimization #OperationsResearch #Gurobi #EnergyTech #FreelanceJobs