FunctionIoT
Job descriptionMeet Our TeamJoin 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.
Location: South Carolina
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