Machine Learning Engineer

Responsibilities

• Run reinforcement learning experiments in physically realistic simulators of mineral processing operations and help turn results into better controllers
• Build and refine pieces of training environments—reward functions, observations, and action logic
• Train control models, track and interpret performance, and investigate underperformance
• Close the gap between simulation and reality by comparing model behavior against real plant data
• Write clean, well-tested code and contribute to services that put models into production
• Partner with process and chemistry experts to understand unit operations

Requirements

• 0–4 years of experience (including internships or research) in machine learning, reinforcement learning, or scientific computing—or a strong recent graduate with demonstrated project depth
• Solid grounding in machine learning fundamentals with working knowledge of modern deep learning; exposure to reinforcement learning is a strong plus
• Proficiency in Python and comfort reading and debugging an existing codebase
• Curiosity about physical, industrial systems and eagerness to learn chemistry and process engineering
• Self-starter who asks good questions, ships, and escalates blockers early

Nice-to-Haves

• Experience with reinforcement learning toolkits used in self-driving vehicles or humanoid robots
• Background in scientific computing or physical systems modeling