What you'll do Build autonomous optimization systems for the real world — connecting AI, control, and process intelligence. Prototype and tune reinforcement learning, model-predictive control, or hybrid physics-ML algorithms.
About you You’re an ML/Control engineer who wants your models to touch the real world. You enjoy writing code that both trains and controls. You’re excited by the challenge of turning industrial data into autonomy.
What we're looking for Familiar with chemical process control, with a chemical engineering background, and has designed interesting DCS programs and controllers. Strong foundation in ML / optimization — e.g., reinforcement learning, MPC, system identification, or Bayesian methods. Understanding of control theory, process systems, or simulation environments is a plus. Experience with real-time data or streaming frameworks (MQTT, OPC-UA, Kafka, etc.) is a plus.