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.

Job Role: 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.

Key Duties:

• 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.

Requirements:

• 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, TensorFlow, 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).

Preferences:

• 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.