Job Description
Responsibilities
- 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
- 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.
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