Vision System Developer

2 weeks ago

Howard Lake, Minnesota, United States Forsman Farms Full time $120,000 - $180,000 per year

We are developing in-house computer vision and machine learning systems to monitor attributes for control system feedback. The systems will detect a variety of quality defects and provide real-time insights to support food safety, production efficiency, and yield. This is a hands-on role responsible for designing and deploying the full stack of hardware, software, and analytics. The ideal candidate has experience building vision systems in industrial or manufacturing environments and can translate data into actionable insights for control systems and/or operations and quality teams.

Key Responsibilities

  • Design and implement vision capture systems including camera setup, lighting considerations, and enclosures suitable for production conditions.
  • Develop, train, and deploy machine learning models for detecting and classifying attributes, with emphasis on practical, real-time performance.
  • Build and manage data pipelines for large-scale image capture, labeling, augmentation, and model training, including workflows for continuous improvement.
  • Deploy models on edge or industrial hardware to support real-time inspection at production line speeds.
  • Design operator interfaces for monitoring system performance, reviewing flagged items, and adjusting thresholds as needed.
  • Integrate vision system outputs with production equipment and control systems, including event logging, reporting, and traceability.
  • Collaborate with production, QA, and engineering teams to validate system performance and ensure alignment with operational goals.
  • Maintain thorough documentation, create test and acceptance plans, and support production rollouts and ongoing maintenance.

Required Qualifications

  • 4+ years of experience designing and deploying computer vision or machine learning systems in a production or industrial setting.
  • Experience with detection, classification, and regression tasks using deep learning frameworks (e.g., PyTorch,TensorFlow).
  • Proficiency in compiled languages for low-latency applications is a plus. (e.g. Python, C++)
  • Familiarity with hardware selection, camera calibration, lighting design, and real-time image acquisition in industrial environments.
  • Experience deploying Machine Learning models on edge or industrial hardware for real-time inference.
  • Knowledge of software engineering best practices: version control containerization CI/CD, and logging/monitoring.
  • Strong problem-solving skills and ability to collaborate with multidisciplinary teams.

Preferred Qualifications

  • Experience in food processing or other high-hygiene manufacturing environments.
  • Familiarity with industrial automation integration (PLCs, I/O protocols).
  • Experience building operator dashboards, configurable thresholds, or visualization tools for quality monitoring.
  • Knowledge of Machine Learning Ops tools and processes for model lifecycle management.

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