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.
