Industrial Vision Architect - IoT Edge Solutions - R
Hitachi Digital Services
Meet Our Team
Join a team at the forefront of Industrial IoT, Edge AI, and Smart Manufacturing, building next-generation vision systems that drive automation, quality, and operational excellence across automotive production environments. Our engineers, architects, and manufacturing specialists collaborate to deliver real-time computer vision solutions that improve product quality, reduce defects, and enable intelligent factory operations. You'll work with cutting-edge edge computing platforms, machine learning technologies, and cloud-native architectures to solve complex industrial challenges at scale.
What You'll Be Doing
Architect and design edge-based computer vision solutions for automotive manufacturing, quality inspection, and industrial automation.
Develop, train, optimize, and deploy machine learning and computer vision models for real-time inference on industrial edge devices.
Design hybrid Edge-to-Cloud architectures leveraging AWS services for model management, monitoring, analytics, and continuous improvement.
Optimize model performance for latency, throughput, memory utilization, and power efficiency across edge hardware platforms.
Build and maintain MLOps and DevOps pipelines for automated model deployment, updates, version control, rollback, and monitoring.
Integrate vision systems with manufacturing technologies including PLCs, MES platforms, factory networks, and industrial control systems.
Lead technical architecture decisions and establish best practices for edge AI, embedded vision, and production-grade deployments.
Collaborate with manufacturing, quality, operations, and engineering teams to deliver scalable and reliable solutions.
Troubleshoot and enhance system performance in high-volume production environments.
Mentor engineers and provide technical leadership across computer vision, machine learning, and edge computing initiatives.
What You'll Bring to the Team
7+ years of software engineering experience with a strong focus on edge computing, embedded systems, or industrial automation.
Expertise in Python and/or C++ development for performance-critical computer vision and machine learning applications.
Strong hands-on experience with computer vision frameworks such as OpenCV and machine learning platforms including PyTorch, TensorFlow, and ONNX.
Proven experience deploying AI/ML solutions on edge hardware platforms such as NVIDIA Jetson, Intel Edge devices, or similar embedded systems.
Experience designing and implementing hybrid AWS architectures that connect edge environments with cloud-based services.
Strong understanding of CI/CD pipelines, DevOps practices, production monitoring, and system reliability engineering.
Experience delivering mission-critical solutions within automotive manufacturing or industrial production environments.
Ability to optimize AI inference workloads for real-time performance and operational scalability.
Strong problem-solving skills with the ability to lead architecture discussions and technical decision-making.
Excellent communication and collaboration skills, with experience mentoring and guiding engineering teams.
Preferred Qualifications
Experience with NVIDIA Tensor RT, CUDA, OpenVINO, or other hardware acceleration frameworks.
Knowledge of industrial communication protocols including OPC UA, MQTT, and Modbus.
Understanding of functional safety standards, validation processes, and production-grade manufacturing systems.
Experience with industrial IoT architectures and connected factory environments.
Familiarity with edge device fleet management, remote deployment, and lifecycle management strategies.
Join a team at the forefront of Industrial IoT, Edge AI, and Smart Manufacturing, building next-generation vision systems that drive automation, quality, and operational excellence across automotive production environments. Our engineers, architects, and manufacturing specialists collaborate to deliver real-time computer vision solutions that improve product quality, reduce defects, and enable intelligent factory operations. You'll work with cutting-edge edge computing platforms, machine learning technologies, and cloud-native architectures to solve complex industrial challenges at scale.
What You'll Be Doing
Architect and design edge-based computer vision solutions for automotive manufacturing, quality inspection, and industrial automation.
Develop, train, optimize, and deploy machine learning and computer vision models for real-time inference on industrial edge devices.
Design hybrid Edge-to-Cloud architectures leveraging AWS services for model management, monitoring, analytics, and continuous improvement.
Optimize model performance for latency, throughput, memory utilization, and power efficiency across edge hardware platforms.
Build and maintain MLOps and DevOps pipelines for automated model deployment, updates, version control, rollback, and monitoring.
Integrate vision systems with manufacturing technologies including PLCs, MES platforms, factory networks, and industrial control systems.
Lead technical architecture decisions and establish best practices for edge AI, embedded vision, and production-grade deployments.
Collaborate with manufacturing, quality, operations, and engineering teams to deliver scalable and reliable solutions.
Troubleshoot and enhance system performance in high-volume production environments.
Mentor engineers and provide technical leadership across computer vision, machine learning, and edge computing initiatives.
What You'll Bring to the Team
7+ years of software engineering experience with a strong focus on edge computing, embedded systems, or industrial automation.
Expertise in Python and/or C++ development for performance-critical computer vision and machine learning applications.
Strong hands-on experience with computer vision frameworks such as OpenCV and machine learning platforms including PyTorch, TensorFlow, and ONNX.
Proven experience deploying AI/ML solutions on edge hardware platforms such as NVIDIA Jetson, Intel Edge devices, or similar embedded systems.
Experience designing and implementing hybrid AWS architectures that connect edge environments with cloud-based services.
Strong understanding of CI/CD pipelines, DevOps practices, production monitoring, and system reliability engineering.
Experience delivering mission-critical solutions within automotive manufacturing or industrial production environments.
Ability to optimize AI inference workloads for real-time performance and operational scalability.
Strong problem-solving skills with the ability to lead architecture discussions and technical decision-making.
Excellent communication and collaboration skills, with experience mentoring and guiding engineering teams.
Preferred Qualifications
Experience with NVIDIA Tensor RT, CUDA, OpenVINO, or other hardware acceleration frameworks.
Knowledge of industrial communication protocols including OPC UA, MQTT, and Modbus.
Understanding of functional safety standards, validation processes, and production-grade manufacturing systems.
Experience with industrial IoT architectures and connected factory environments.
Familiarity with edge device fleet management, remote deployment, and lifecycle management strategies.
Reference: 3157014365