Edge AI/ML Practice Lead

Role & responsibilities

Job Title / Designation : Practice Lead AI/ML

Business Unit : Embedded Engineering Services (EES)

Industry Experience Range : 8+ years

Job Location : Preferably Pune or Bangalore, Ahmedabad

Shift : General Shift (Mon-Fri)

Job Function, Roles & Responsibilities:

• Lead strategic initiatives and own the practice for Edge AI/ML, data pipelines, and intelligent embedded systems
• Define and build the competency roadmap for machine learning, deep learning, model deployment, and real-time inferencing on edge platforms
• Oversee data creation including data collection, dataset curation, annotation, cleaning, augmentation, and synthetic data generation
• Champion use cases involving sensor fusion, combining data from multiple sources (vision, IMU, radar, audio, etc.) to create robust, efficient, and context-aware edge intelligence solutions
• Drive edge analytics and on-device learning across verticals such as Industrial Automation, Medical Devices, Automotive, and Smart Consumer Electronics
• Collaborate with global customers to gather requirements, architect solutions, track project delivery, and ensure alignment with business objectives
• Support business development with presales solutioning, proposal writing, and effort estimation
• Drive internal capability building through mentoring, training, and competency development

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Preferred candidate profile:

8+ years in embedded systems, AI/ML, and data engineering, with a strong focus on edge intelligence and real-time systems. At least 3 years in a technical leadership or strategic role. Prior experience in a product engineering services environment preferred.

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Area of Expertise:

• Proven expertise in deploying ML/DL models on edge devices (NVIDIA Jetson, NXP i.MX, Qualcomm QCS, TI Sitara, etc.)
• Strong knowledge of data workflows: dataset generation, manual/automated annotation, data cleaning, augmentation, and synthetic data creation
• Deep understanding of sensor fusion techniques combining inputs from vision, audio, IMU, radar, LIDAR, and other sources to improve model accuracy and efficiency
• Experience in model optimization using TensorRT, ONNX, OpenVINO, TFLite, and TVM
• Hands-on with TensorFlow, PyTorch, scikit-learn, and signal/image processing techniques
• Proficient in designing for real-time inference on resource-constrained platforms
• Exposure to AI accelerators, NPUs, DSPs, and hybrid SoC environments; must have exposure to NVIDIA SoC & Tools
• Presales, account engagement, and solutioning experience with North American or European clients

Please share resume at anup.s@acldigital.com, candidate can directly call on cell number 99099-75421 for more details.