Edge AI/ML Practice Lead

1 week ago

Ahmedabad Bengaluru Pune, India ACL Digital Full time ₹ 15,00,000 - ₹ 20,00,000 per year

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

________________________________________

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.

________________________________________

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 , candidate can directly call on cell number for more details.

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