[Remote] Edge AI Principal
Note: The job is a remote job and is open to candidates in USA. HCLTech is looking for a highly talented and self-motivated Edge AI Principal to join it in advancing the technological world through innovation and creativity. The role involves leading the design, architecture, development, and scaled deployment of real-time AI and robotics solutions that operate at the edge, leveraging state-of-the-art technology across multiple industries.
Responsibilities
- Lead the end-to-end design and architecture of edge AI solutions , combining robotics, computer vision, and AI inference deployed on heterogeneous edge devices
- Architect hybrid AI workflows spanning edge, near-edge, and cloud environments , ensuring low-latency, high-reliability inference
- Build scalable AI and robotics workflows supporting real-time decision-making and autonomy in complex environments
- Develop architecture for multi-site, distributed deployments with integration into operational technology (OT) systems like SCADA, MES, and healthcare devices
- Drive hybrid edge-to-cloud AI deployments optimizing latency, throughput, and cost
- Lead the development and deployment of robot policies, task planning, and intelligent automation using AI techniques like reinforcement learning, hierarchical planning, and sensor fusion
- Oversee computer vision model development for perception tasks such as object detection, tracking, quality inspection, and anomaly detection optimized for edge inference
- Implement robotics simulation and real-world testing pipelines using platforms like NVIDIA Isaac Sim, Gazebo, or MuJoCo to validate policies and control algorithms
- Optimize AI and robotics models for target edge hardware with pruning, quantization, and GPU acceleration (TensorRT, CUDA)
- Utilize NVIDIA Jetson, IGX, EGX platforms and toolkits including NVIDIA Isaac, DeepStream, Metropolis, Holoscan, and the NGC software catalog for AI and robotics deployment
- Integrate hyperscaler edge AI offerings : AWS IoT Greengrass, Lambda@Edge, SageMaker Edge Manager; Azure IoT Edge, Percept, Azure Stack HCI; GCP Vertex AI, TensorFlow Lite for seamless edge-cloud orchestration
- Leverage OEM edge infrastructure from Dell NativeEdge and HPE Edgeline servers for ruggedized and scalable edge computing environments
- Design patterns for edge networks, data aggregation, and processing. Familiarity with hardware accelerators (TPUs, GPUs, FPGAs) and embedded systems
- Docker, Kubernetes for edge device orchestration
- Knowledge of fog computing layers and the relationship with edge/cloud environments
- Apache Kafka, Apache Flink, Apache Spark (for distributed data processing on the edge)
- Architect secure, robust AI/robotics model lifecycle management for fleet-wide OTA updates, monitoring, automated rollback, and anomaly detection
- Design and enforce edge security, privacy, and compliance strategies suitable for industrial, healthcare, and transportation domains
- Collaborate with cross-functional teams including embedded, hardware, software, and data science to deliver end-to-end operational AI robotic solutions
- Develop reusable IP including reference architectures, accelerators, APIs, and demo kits for common robotics and edge AI industrial use cases
- Mentor technical teams on cutting-edge edge AI, robotics frameworks, simulation, deployment best practices, and compliance
- Evangelize edge AI and robotics capabilities internally and externally through presentations, workshops, and collaboration with technology partners
- Act as a trusted advisor to clients and stakeholders, translating business challenges into technically feasible edge AI and robotics solutions
- Engage with NVIDIA, hyperscalers, OEMs, and ecosystem partners to stay current on emerging technologies and co-develop joint solutions
Skills
- Experience in software, AI architecture or robotics engineering with leading edge AI and robotics deployments at scale across Manufacturing, Oil & Gas, Transportation, Healthcare, or related industries
- Proven track record of designing, deploying, and scaling real-time AI and robotics systems on edge platforms (NVIDIA Jetson, IGX, EGX)
- Hands-on experience with robotics middleware (e.g., ROS), simulation tools (Isaac Sim, Gazebo), and AI frameworks (TensorFlow, PyTorch)
- Experience integrating edge AI solutions with industrial OT and healthcare systems
- Proficiency with Python, C++, and ML/DL frameworks (TensorFlow, PyTorch)
- Deep expertise in robotics: task & motion planning, policy learning, sensor fusion (camera, LiDAR, IMU), robot control & kinematics
- Strong computer vision skills in model development for detection, classification, segmentation, and video analytics
- Proficiency in CUDA, TensorRT, DeepStream for model optimization on GPUs
- Familiarity with containerization (Docker), orchestration (Kubernetes), CI/CD pipelines tailored for edge deployments
- Knowledge of edge security, privacy-preserving AI, and regulatory compliance (HIPAA, GxP, ISO standards)
- Knowledge of Networking Protocols: TCP/IP, UDP, Bluetooth, Zigbee, LoRaWAN, NB-IoT, and 5G networks
- Low Power Communication: LPWAN (Low Power Wide Area Network) technologies like LoRa, NB-IoT
- NVIDIA Robotics & Edge AI stack, hyperscaler edge solutions (AWS IoT Greengrass, Azure IoT Edge, GCP Vertex AI)
- OEM rugged edge platforms like Dell NativeEdge, HPE Edgeline
- Bachelor's/Master's degree in Robotics, Computer Science, Electrical Engineering, or related field (PhD preferred)
- Relevant certifications from NVIDIA DLI, hyperscalers, or robotics platforms beneficial
- Experience with deployment in brownfield industrial/clinical environments with complex safety and compliance requirements
- Thought leadership with publications or patents in robotics, edge AI, or computer vision
- Demonstrated ability to lead multi-disciplinary, global teams and foster innovation culture
Benefits
- Medical
- Dental
- Vision
- Pharmacy
- Life
- Accidental death & dismemberment
- Disability insurance
- Employee assistance program
- 401(k) retirement plan
- 10 days of paid time off per year
- 10 paid holidays per year
Company Overview
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