AIO Engineer

About the role

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.

Key responsibilities

• Build autonomous optimization systems connecting AI, control, and process intelligence
• Prototype and tune reinforcement learning, model-predictive control, or hybrid physics-ML algorithms
• Write code that both trains and controls
• Turn industrial data into autonomy

About you

• ML/Control engineer who wants models to touch the real world
• Familiar with chemical process control with a chemical engineering background
• 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
• Experience with real-time data or streaming frameworks (MQTT, OPC-UA, Kafka, etc.)

In order for us to better evaluate your application, kindly attach your projects (website/github repo/pdf etc) with resume.