• Architect and develop scalable ML and AI solutions, aligning model design and deployment with product and customer needs.
• Build, train, and optimize machine learning models using Python, ML frameworks, and large‑scale data pipelines.
• Leverage PyTorch, ML SDKs, and GPU‑accelerated workflows to support advanced model development and experimentation.
• Work with large, complex datasets to design robust feature engineering, data processing, and model evaluation approaches.
• Collaborate cross‑functionally with engineering, analytics, finance, and professional services stakeholders to deliver end‑to‑end ML solutions.
• Participate in the design of ML system architecture, ensuring reliability, quality, and operational efficiency.
• Research emerging AI/ML technologies and integrate new capabilities that strengthen Epicor’s long‑term data science strategy.

What you will likely bring:

• 6+ years’ experience building, deploying, and supporting large‑scale analytics, ML, or AI solutions.
• Advanced proficiency in Python, including development of production‑grade ML models.
• Experience with PyTorch, ML SDKs, and modern machine learning frameworks.
• Demonstrated success working with large datasets and architecting scalable data science workflows.
• Experience designing ML system architecture and end‑to‑end data science solutions.
• Applied analytics experience with strong analytical thinking and problem‑solving skills.
• Experience collaborating across technical and non‑technical teams to drive ML‑driven outcomes.

What could set you apart:

• Experience with GPU‑accelerated ML workflows.
• Familiarity with R for data science or analytics research.
• Experience writing or interpreting ML/AI whitepapers or applied research.
• Exposure to big data pipelines and distributed compute environments.
• Background collaborating with finance or professional services teams on data‑driven initiatives.