Location
Waukesha, WI
Salary
Not specified
Type
fulltime
Posted
Today
Job Description
The AI Applications Engineer will design, develop, and deploy scalable AI/ML solutions that accelerate digital transformation across manufacturing operations. This role will focus on translating operational challenges into deployable AI solutions—integrating operations platforms to enable smarter decision-making, automation, and predictive insights. This position plays a critical role in building the “Digital Factory \+ AI” capability stack.
This position could include up to 25% travel locally.
**Major Responsibilities:**
AI Solution Development \& Deployment
- Design, build, test, and deploy machine learning and AI models, including productionizing solutions and maintaining model performance over time.
Manufacturing (Operations) Use Case Delivery
- Develop and support AI solutions for shop floor applications such as predictive maintenance, quality inspection, yield optimization, and throughput improvement.
Data Engineering \& Platform Integration
- Develop data pipelines, integrate with enterprise systems, and ensure scalable, reusable AI and data architecture.
Cross-Functional Collaboration \& Business Translation
- Partner with Operations and IT teams to define use cases, translate business problems into AI solutions, and ensure adoption. Including build vs. buy analysis.
Continuous Improvement, Governance \& Documentation
- Monitor model performance, ensure data/model governance, document solutions, and drive reusability and standardization across sites/functions.
**Minimum Job Requirements:**
Education
- Bachelor’s degree in computer science, engineering, data science, or related field
**Work Experience**
- Experience working with structured and unstructured data
- Experience building and deploying AI based vision systems
- 5 years in manufacturing / OT environments, PLC, SCADA, MES exposure
- 2 years of experience in AI/ML development and deployment
**Knowledge / Skills / Abilities**
- Python (TensorFlow, PyTorch, Scikit-learn)
- Data engineering and ETL pipelines
- Model deployment (APIs, microservices, Docker, etc.)
- Understanding of industrial systems, manufacturing processes, or IoT data
- Strong problem-solving and systems thinking mindset
- Ability to bridge technical and business domains
- Execution-focused with a bias toward deployment (not just modeling)
- Ability to work across operations, engineering, and service functions
- Ability to demonstrate clear communication with both technical teams and leadership
**Preferred Job Requirements:**
Education
- Master’s Degree
**Work Experience**
- Experience in discrete manufacturing environments
- Experience working in digital factory or Industry 4\.0 initiatives
- Familiarity with MES, PLM, and ERP integrations (SAP, Tulip, Windchill, etc.)
Knowledge / Skills / Abilities
- Experience with Computer vision (OpenCV, vision models
- Time-series analysis (sensor, telemetry data)
- Edge AI deployment
Looking for more opportunities?
Browse thousands of graduate jobs and entry-level positions.