Position: Data Scientist / Machine Learning Engineer
About Our Client: Our client is an innovative startup Supported by leading institutions, they develop machine learning-driven software solutions that streamline complex industrial processes.
Role Overview: We are seeking a skilled Data Scientist / Machine Learning Engineer to develop and deploy an RL controller aimed at minimising losses in the production line. This role involves creating a digital twin of the production line, training the RL controller, and deploying it to optimise production efficiency.
Key Responsibilities:
* Parse real-time measurements from the production line, including temperatures, pressures, setpoints, and process variables.
* Develop a digital twin of the production line to simulate and analyse production processes.
* Design and train a Reinforcement Learning controller to take actions that minimise the loss function.
* Deploy the trained RL controller on the production line and monitor its performance.
* Collaborate with cross-functional teams to integrate the RL controller into existing systems.
Qualifications:
* Proven experience in developing and deploying machine learning models, particularly in industrial settings.
* Strong proficiency in Python and experience with deep learning frameworks such as PyTorch or Jax.
* Experience with Reinforcement Learning algorithms and their application in real-world scenarios.
* Familiarity with data acquisition and processing from industrial systems.
* Ability to write production-quality code and utilise modern development tools and methodologies (e.g., version control, CI/CD, containers) within cloud platforms like GCP, AWS, or Azure.
Preferred Experience:
* Knowledge of process control or industrial operations.
* Background as a founder or early-stage engineer in a startup environment.