Staff Computer Vision Engineer

Job Description *** This role is hybrid in our Chicago headquarters and requires the ability to travel to manufacturing sites across North America *** Here at Kraft Heinz, we grow our people to grow our business, because we believe that great people make great companies. When you join our table, you can expect access to an array of holistic wellness benefits* and perks, including medical, dental and vision coverage, 7% 401(k) matching, Business Resource Groups (BRGs) to help foster diversity, inclusion, and belonging for all employees, an industry-leading total rewards package that emphasizes a high discretionary bonus. *Benefits begin immediately upon hire for salaried employees. Get a peek into life here at Kraft Heinz through our  Instagram  and  TikTok  channels! Staff Computer Vision Engineer at a glance... You will lead the design, development, deployment, and scale-up of advanced computer vision and edge AI solutions across manufacturing and supply chain environments. You will be a subject matter expert responsible for solving complex industrial vision challenges spanning hardware, software, machine learning, networking, operational technology, and cloud environments. You will partner with engineering, manufacturing, quality, operations, IT, cloud, and analytics teams to develop production-grade solutions that deliver measurable business value, while leading technical initiatives, influencing architecture, and mentoring technical professionals without direct people-management responsibility What's on the menu? Design, train, evaluate, and deploy computer vision models for real-world manufacturing applications. Develop solutions involving object detection, classification, segmentation, OCR, anomaly detection, tracking, and multimodal AI. Define model performance measures and business-focused success criteria appropriate for plant operations. Design robust data, experiment, and validation methodologies for production environments. Design complete machine vision solutions incorporating cameras, sensors, lenses, illumination, triggers, industrial networking, and edge computing. Select imaging hardware based on field of view, spatial resolution, working distance, motion, lighting, environmental constraints, and production requirements. Deploy machine learning and computer vision workloads to edge computing platforms. Build, optimize, and maintain Docker images and containerized deployment workflows. Deploy and support applications on Linux-based systems and NVIDIA Jetson platforms using the JetPack ecosystem. Recipe for Success - apply now if this sounds like you! I have a Master's degree or PhD in Computer Science, Computer Engineering, Electrical Engineering, Data Science, Applied Mathematics, Robotics, or related technical field, or equivalent research and professional experience. I have years of relevant professional or applied research experience in computer vision, machine learning, machine vision, robotics, industrial automation, or related disciplines. I have demonstrated experience leading technically complex projects with meaningful operational or business impact. I have deep expertise in computer vision, deep learning, and machine learning methods. I have advanced proficiency in Python and experience developing production-quality technical solutions. I have strong Linux development and administration experience, including command-line workflows, SSH, SCP, remote troubleshooting, and system configuration. I have hands-on experience building Docker images, managing containers, and deploying containerized applications to edge or production environments. I have experience deploying and supporting AI/ML solutions in production, including cloud environments such as Azure, AWS, or GCP. I have experience integrating hardware, networking, IoT, and software components into end-to-end systems. I have the ability to communicate clearly with technical and non-technical stakeholders and operate effectively when