AI Vision Machine Learning Engineer
About The Position
The AI Vision Machine Learning Engineer designs and implements analytical models that extract insights from static images and video in a manufacturing environment. The role focuses on object measurement, classification, anomaly detection, and predictive and recommendation algorithms that deliver measurable business value. The engineer communicates benefits to stakeholders to encourage adoption and prioritize operationalization. The position develops and refines deep learning models for manufacturing perception tasks, optimizes and deploys models to edge devices, and integrates them with factory systems in collaboration with the control systems team. It also uses cloud infrastructure for model training, deployment, governance, and downstream data availability. The engineer works with manufacturing and process engineering teams to address operational needs, monitors model performance with BI tools, and develops validation and retraining plans. The role contributes to data science, reporting, governance, data quality, and data management initiatives across the analytics ecosystem. It also collaborates with procurement and external suppliers, keeps current with relevant technologies, and communicates opportunities and business value to users and leaders.
Requirements
- 3–5 years of experience in computer vision, image analytics, or a related field, including at least 2 years in a manufacturing context.
- Proven track record of deploying models in production environments.
- Working knowledge of Spotfire Analytics, Power BI, or a similar data visualization tool.
- Strong proficiency in computer vision techniques, such as OpenCV, TensorFlow, and PyTorch.
- Knowledge of machine vision systems and related hardware, including cameras, optics, lighting, IoT, and networking.
- Expertise in image and video processing, including feature extraction, classification, edge finding, and morphology.
- Solid understanding of predictive modeling techniques and model governance.
- Programming skills in Python, C++/C#, or similar, and familiarity with visual analytics libraries and code and task management tools such as GitHub and DevOps.
- Ability to build user-friendly interfaces using storytelling techniques.
- Ability to explain technical concepts in business terms and influence decision-making.
- Excellent problem-solving and analytical thinking, with an emphasis on product development.
- Excellent written and verbal communication skills for coordinating across teams.
- Curiosity and willingness to explore and fail.
- High initiative and a bias for action.
- BS, MS, or PhD in computer science, data science, engineering with a software focus, or a closely related field.
Nice To Haves
- Master’s degree or above is preferred.
- Advanced Power BI, Spotfire, or similar BI tool development and dashboarding experience.
- Experience with a wide array of camera, lighting, IoT integration, and edge computing solutions.
- Experience with manufacturing or industrial environmental requirements affecting hardware selection.
- Familiarity with SCADA systems, with a strong preference for Ignition.
- Experience in industrial metrology, product quality, and/or chemical manufacturing.
- Familiarity with business reporting and common business KPIs.
- Statistical modeling and advanced analysis techniques.
- Ability to build collaborative relationships.
- Ability to influence through storytelling.
Responsibilities
- Develop, train, and refine deep learning models for automated perception tasks, including object detection, classification, measurement, and anomaly identification.
- Optimize and deploy trained models to edge devices in manufacturing environments, collaborating with the control systems team.
- Use cloud infrastructure as appropriate for model training, deployment, governance, and downstream data availability.
- Partner with manufacturing and process engineering teams to ensure models address operational needs and are operationalized in production workflows.
- Communicate the value of models to stakeholders and support adoption and prioritization.
- Report and monitor model performance using BI tools, communicate actionable insights, and develop optimization, validation, and retraining plans.
- Collaborate with Data & Analytics team members on data science model building, model management, and deployment.
- Work with procurement and external suppliers to access expertise in technologies and integration capabilities.
- Support data science, enterprise reporting, governance, data quality, data management, and Community of Practice initiatives.
- Monitor industry developments in data management, visualization, modeling, visual analysis, and integration technologies, and communicate their potential value.
- Identify opportunities to apply machine vision analytics in new ways and communicate business value to users and leaders.
Benefits
- Medical insurance may be available, depending on hours worked.
- Dental insurance may be available, depending on hours worked.
- Vision insurance may be available, depending on hours worked.
- 401(k) plan may be available, depending on hours worked.
- Variable bonus may be available, depending on hours worked.
- Life insurance coverage may be available, depending on hours worked.
- Disability benefits may be available, depending on hours worked.
- PTO may be available, depending on hours worked.
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
