Lead Machine Learning Engineer

Innovative Refrigeration Systems, Inc. is looking for a results‑oriented Lead Machine Learning Engineer to join our Software Engineering Department full‑time onsite in Waynesboro, VA. This role is pivotal in developing advanced machine learning models that optimize energy efficiency across large‑scale industrial refrigeration and cold storage facilities.

Our aim is to create a more sustainable future for our Fortune 1000 clients powering America’s food supply chain. This is an extremely rewarding and impactful greenfield initiative with a company uniquely positioned to challenge the status quo.

The Lead Machine Learning Engineer will design, develop, and deploy ML‑driven optimization systems that integrate with industrial PLC and IoT data streams. This role bridges mechanical and data science disciplines to enhance performance and sustainability of refrigeration systems.

• Build physics‑based and reinforcement learning models to improve energy efficiency and temperature safety in industrial refrigeration systems.
• Fine‑tune, test, and deploy machine learning models to production environments.
• Collaborate with product, energy, and software teams to influence platform architecture and features.
• Analyze large datasets from industrial sensors, controls, and process systems.
• Develop predictive models for maintenance and performance optimization.
• Document algorithms, workflows, and performance metrics for ongoing improvement.

• Bachelor’s degree in Computer Science, Computer Information Systems, Data Science, Mechanical, Chemical, or Electrical Engineering (or equivalent experience).
• Minimum 2 years of hands‑on experience building and optimizing ML systems.
• Strong understanding of machine learning theory and practical model deployment.
• Experience working in cloud ML environments (AWS, Azure, or GCP).
• Proficient in ML tools such as Python, Tensor Flow, Scikit‑learn, or R.
• Excellent problem‑solving and collaboration skills.
• Self‑starter with the ability to learn mechanical engineering principles related to refrigeration and thermodynamics. Must be able to remain in a stationary position (seated or standing) for extended periods.
• Occasionally may need to lift or carry items up to 25 pounds (e.g., office supplies, small equipment).

• Master’s or PhD in Computer Science, Mathematics, or Engineering.
• Background in energy optimization, predictive maintenance, thermodynamics, or industrial refrigeration.
• Prior software engineering experience building backend systems around ML models.

• Mid‑Senior level

• Full‑time

• Engineering and Information Technology

• Industrial Machinery Manufacturing