Senior Engineer – Computer Vision Edge Intelligence & Embedded Systems
About the Role We are seeking a highly skilled and experienced Senior AI & Computer Vision Engineer to lead the
design, development, and deployment of intelligent edge AI systems. This role is pivotal in elevating
our AI team’s capabilities by driving architectural excellence, ensuring adherence to best practices in
AI/ML and computer vision, and enabling scalable, efficient, and robust edge deployments on low-
power hardware platforms such as NVIDIA Jetson and Orin series devices.
The successful candidate will be responsible for end-to-end solution design—ranging from model
selection and optimization to MLOps integration and real-time inference deployment—while
maintaining strict performance, power, and latency constraints typical of edge environments.
Key Responsibilities • Architect and implement high-performance, low-latency AI/Computer Vision systems
tailored for edge deployment on NVIDIA Jetson and Orin platforms.
• Lead the selection, development, and optimization of computer vision models (e.g., object
detection, segmentation, tracking) for real-time inference under constrained power and
compute budgets.
• Design and manage MLOps pipelines for model training, validation, continuous integration,
and deployment to edge devices, ensuring reproducibility, version control, and monitoring.
• Conduct hardware-software co-design to balance performance, power consumption, and
thermal efficiency in embedded systems.
• Evaluate and recommend optimal hardware configurations, software frameworks (e.g.,
TensorRT, ONNX, OpenCV), and inference engines for edge deployment.
• Mentor junior engineers on AI best practices, model architecture, and edge deployment
strategies to elevate team capability.
• Define and enforce standards for model accuracy, inference speed, memory footprint, and
energy efficiency across all edge AI projects.
• Collaborate with cross-functional teams (hardware, firmware, product) to integrate AI
solutions into production systems with minimal latency and maximum reliability.
Required Qualifications & Experience • Bachelor’s degree in Computer Science, Electrical Engineering, Robotics, or related field;
Master’s or PhD preferred.
• Minimum 5 years of hands-on experience in AI/Computer Vision, with at least 3 years
focused on edge AI and embedded systems.
• Deep expertise in computer vision algorithms (e.g., YOLO, EfficientDet, SegFormer, Pose
Estimation) and model optimization techniques (quantization, pruning, distillation).
• Proven experience deploying AI models on NVIDIA Jetson (e.g., Jetson Nano, TX2, AGX Orin)
and Orin series devices.
• Strong proficiency in MLOps tools and workflows (e.g., MLflow, Kubeflow, CI/CD for AI, model
registry, containerization with Docker).
• Experience with inference engines (TensorRT, ONNX Runtime) and low-level optimization for
power efficiency.
• Familiarity with real-time systems, latency-sensitive applications, and power-aware design
principles.
• Demonstrated ability to lead technical design, conduct peer reviews, and guide team-wide
technical standards.
• Excellent communication skills and ability to translate technical concepts for stakeholders.
Mandatory Skills • Experience with edge AI frameworks (e.g., NVIDIA DeepStream, OpenVINO, TensorFlow Lite).
• Knowledge of hardware acceleration (e.g., CUDA, Tegra, NPU) and thermal management
strategies.
• Experience in autonomous systems, robotics, or smart vision systems in industrial or
consumer applications.