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The Kraft Heinz Company
The Kraft Heinz Company
B2CFood & BeverageRetail
The Kraft Heinz Company is a global food and beverage business with a broad portfolio of well-known consumer brands. Its products span everyday eating occasions, serving customers at home, in restaurants, and on the go. The company operates across B2C, food and beverage, and retail markets, with a large international workforce focused on shaping the future of food.
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Staff Computer Vision Engineer — Chicago Hybrid

Lead production computer vision and edge AI solutions that improve manufacturing and supply chain operations at Kraft Heinz. This Chicago-based hybrid role spans machine learning, industrial vision, and deployment on edge platforms.

USUnited StatesILIllinois
$120,800 – $151,000 / year
HybridFull-timeLeadEnglish RequiredComputer Vision EngineerMachine Learning Engineer
AWSAzureCloudDockerGoogle Cloud PlatformIoTLinuxPython

Description

  • Lead the development, deployment, and expansion of computer vision and edge AI systems across manufacturing and supply chain operations
  • Address complex industrial vision problems across hardware, software, machine learning, networking, operational technology, and cloud platforms
  • Work with engineering, manufacturing, quality, operations, IT, cloud, and analytics teams to deliver production systems with measurable business impact
  • Drive technical programs and shape solution architecture
  • Mentor technical colleagues without direct personnel-management duties
  • Create, train, assess, and deploy computer vision models for manufacturing use cases
  • Build solutions using object detection, classification, segmentation, OCR, anomaly detection, tracking, and multimodal AI
  • Establish model metrics and business-oriented success criteria for plant operations
  • Develop data, experimentation, and validation approaches suited to production environments
  • Create end-to-end machine vision systems using cameras, sensors, lenses, lighting, triggers, industrial networks, and edge computing
  • Choose imaging hardware according to field of view, spatial resolution, working distance, motion, lighting, environmental conditions, and production needs
  • Deploy machine learning and computer vision workloads to edge computing systems
  • Create, optimize, and maintain Docker images and container-based deployment processes
  • Deploy and support applications on Linux systems and NVIDIA Jetson devices through the JetPack ecosystem

Requirements

  • Master’s degree or PhD in computer science, computer engineering, electrical engineering, data science, applied mathematics, robotics, or a related technical discipline, or equivalent research and professional experience
  • Relevant professional or applied research background in computer vision, machine learning, machine vision, robotics, industrial automation, or a related field
  • Track record of leading technically complex initiatives with significant operational or business results
  • Advanced knowledge of computer vision, deep learning, and machine learning techniques
  • Advanced Python programming skills
  • Strong Linux development and administration experience, including command-line tools, SSH, SCP, remote diagnosis, and system configuration
  • Practical experience creating Docker images, managing containers, and deploying containerized software to edge or production systems
  • Experience delivering and supporting production AI/ML solutions on Azure, AWS, or GCP
  • Experience combining hardware, networking, IoT, and software into integrated end-to-end systems
  • Clear communication with technical and non-technical stakeholders, including the ability to work productively amid unclear requirements

Benefits

  • Medical, prescription, dental, and vision insurance
  • 7% 401(k) contribution match
  • Business Resource Groups (BRGs)
  • Performance-based bonus
  • Physical, social, emotional, and financial wellbeing events, resources, and learning opportunities
  • Paid time off
  • Company holidays
  • Leave of absence
  • Flexible work arrangements
  • Employee recognition programs
  • Training opportunities
  • Employee Assistance Program
  • Wellbeing programs
  • Family support programs
  • Life insurance
  • Accidental Death & Dismemberment coverage
  • Disability coverage

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