Role & Responsibilities:

- Design, Develop and Optimize AI/ML models (e.g., CNNs, transformers) for edge devices using hardware accelerators like GPU, DSP, and NPU.

- Analyze performance & identify bottlenecks and tune inference pipelines for memory, power, and compute efficiency.

- Adapt and integrate optimized models to inference runtimes such as TensorRT, ONNX, TFLite, SNPE, OpenVINO, or TVM.

- Implement quantization, pruning, and other model compression techniques.

- Support for integration of AI workloads into embedded software stacks running on Linux, RTOS, or bare-metal systems.

- Participate in the team's software processes to ensure code quality & maintenance, including -- requirements and design documentation, test-plan generation and execution, peer design and code reviews

- Stay current with advancements in edge computing, AI inference frameworks, and compiler toolchains.

Required skills / Whom we are looking for:

- Bachelors or Masters degree in related engineering field with 4 to 8 years of hands-on experience in experience in embedded AI/ML development, with a focus on model optimization and deployment.

- Proficiency in in C/C++ and Python programming, Intrinsic or Assembly based optimization methods using instruction pipeline and latency optimal designs, Modular and Object-Oriented programming skills





- Experience working with heterogeneous computing platforms (e.g., CPU + GPU/DSP/NPU). Must have exposure and development experience on one or more DSPs/NPUs for example ARM-NEON, TI C6x/C7x DSP, Tensilica Vision DSPs, CEVA DSPs, Qualcomm Hexagon HVX DSP

- In-depth knowledge Processor/SoC architecture – VLIW and SIMD, DMA, cache, memory architecture etc.,

- Working experience in machine learning technologies such as CNN, transformers, quantization algorithms and approaches on embedded systems

- Hands-on experience with any of the AI frameworks such as TensorFlow, PyTorch, or ONNX and familiarity with inference toolkits such as TensorRT, SNPE, TFLite, TVM, or OpenVINO.

- Familiarity with build systems (e.g. make, cmake, GCC, Eclipse, Visual Studio, ARM Development Tools)

- Familiarity with debugging tools such as GDB, JTAG, and performance profiling tools.

- Well verse with software development life cycle and efficient use of associated tools like Git, SVN, JIRA etc.,

- Strong communication skills and the ability to work effectively in a cooperative, cross-functional team environment.

- Detail-oriented with a focus on delivering high-quality, reliable software.

- Self-motivated with a strong passion for embedded AI systems and technology.

📌 Edge AI Engineer (Bengaluru)
🏢 Vedya Labs
📍 Bengaluru