Edge AI Solutions Architect

Job Title / Designation: Technical Lead/ Senior Technical Lead, Embedded Engineering Services (EES)

Experience Range: 8 to 12 Years

Job Location: Ahmedabad

Shift: General Shift (Mon-Fri)

Job Function, Roles & Responsibilities:

● Expertly execute and technically lead multiple concurrent projects, ensuring successful delivery.

● Provide hands-on programming, coding, and debugging support as needed.

● Technically lead and mentor a team of 8-10 engineers, continuous development to enhance efficiency and meet customer requirements.

● Serve as primary customer facing resource, driving requirements technically and showcasing the value addition.

● Full knowledge of entire SDLC - Requirement, Design, Development, Reviews, Testing, Deployment, Bug Fixing

● Review & Documentation - PRS, Design, Test Plan/Test Cases

● Actively participate in building and mentoring team members for capability growth.

● Contribute to new candidate interviewing and evaluation processes.

● Collaborate closely with Subject Matter Experts (SMEs) and Centers of Excellence (COEs) on activities such as:

○ Analyzing the competitive ecosystem, identifying technology gaps, and understanding customer needs.

○ Attending industry events, participating in technical qualification calls with Sales, and technically driving those discussions.

○ Define and execute internal Proof of Concepts (POCs) for capability building and technical positioning.

○ Work with the bid management team to develop detailed proposals and contribute to winning new business.

Area of expertise:

● Minimum of 3 years of hands-on Machine Learning experience specifically on Edge Devices.

● Led an edge AI platform team for various US or Europe based customers.

● Proficiency in programming languages such as Python, C, and C++, with a focus on embedded systems development.

● Strong understanding of fundamental machine learning algorithms and techniques, including regression, classification, clustering, and various neural networks.

● Proven expertise in deploying ML/DL models on various edge platforms - NVIDIA Jetson, NXP, STM, Qualcomm, TI Sitara, Synaptics platforms.

● Experience with Model data management, Model quantization techniques, Inference optimization for constrained environments.

● Hands-on experience with key machine learning libraries and frameworks, including PyTorch, TFLite, TensorFlow, ONNX, and tinyML.

● Experience with computer vision and multimedia libraries, including OpenCV, Gstreamer, CUDA APIs, Alsa, and PulseAudio, as well as audio and video codecs.

● Exposure to and experience with AI accelerators, NPUs (Torque, eIQ, Ethos U55, etc.), DSPs, and hybrid System-on-Chip (SoC) environments.

● Strong knowledge of end-to-end data workflows: dataset generation, manual/automated annotation, data cleaning, augmentation, and synthetic data creation.

● Deep understanding of sensor fusion techniques, effectively combining inputs from sources like vision, audio, IMU, radar, and LIDAR to enhance model accuracy and efficiency.

● Experience with data storage and processing technologies (e.G. SQL, JSON, XML).

● Proficient documentation skills for design, architecture, and release notes.

● Excellent problem-solving and analytical skills.

● Good knowledge on Git & CI/CD

Soft Skills:

● Write high-quality, efficient, extensible, and maintainable code in a fast-paced Agile environment

● Participate in feature and design discussions within and across teams

● Evangelize and inform with well-written design documents and conduct peer reviews

● Review code, develop documentation and capacity plans, and debug the hardest problems live on some of the most innovative IoT devices

● Excellent written and verbal communication

Educational Criteria:

BE/ME/B.Tech/M.Tech – Electronics / Electronics & Communications

Travel:

We expect flexibility to travel to the customer locations within or outside India on business trips and short deployments.

If you believe you are a good match for our requirements outlined above, please send your latest resume with below-mentioned details:

Total Experience (years) :

Relevant Experience (years) :

Current CTC (INR) :

Expected CTC (INR):