ACL Digital - Solution Architect - Deep Learning/Machine Learning

Description :

Below are job details :

Job Title / Designation : Project Manager to Associate Director based on experience & expertise.

Business Unit : Embedded Engineering Services (EES).

Industry Experience : 10+ years.

Job Location : Preferably Pune.

Shift : General Shift (Mon-Fri).

Job Function, Roles & Responsibilities :

- 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.

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.

Nice to Have :

- Cloud-edge integration using AWS Greengrass, Azure IoT Edge, GCP Edge TPU.

- Understanding of AI regulatory/safety standards (ISO, IEC, FDA compliance for AI/ML in regulated industries).

Educational Criteria :