Embedded Machine Learning Engineer

Company Description PowaiILabs Technology Pvt Ltd (Powai Labs) is one of India’s pioneering home-grown EDA and processor technology companies, founded within the IIT Bombay campus and backed by its incubator SINE. Originating as a research program in 1999, the company has evolved into a strong collaboration between industry, academia, and government, focused on innovation in electronic system and design automation. Powai Labs builds tools such as simulation accelerators, emulators, and FPGA visibility solutions that help global semiconductor and system design teams improve verification efficiency and time-to-market. With a deep research heritage and entrepreneurial culture, the company is committed to creating high-value, cost-effective technology from India for global markets. Individuals passionate about next-generation EDA, processors, and high-impact R&D will find opportunities to innovate at the intersection of academia and industry.
Role Description As an Embedded Machine Learning Engineer at Powai Labs, you will design, implement, and optimize machine learning models for deployment on embedded and edge hardware platforms. You will work closely with FPGA, ASIC, and system design engineers to integrate ML-based algorithms into existing workflows, focusing on performance, resource utilization, and reliability. Daily responsibilities include researching suitable ML techniques, developing and testing algorithms, profiling and optimizing code for embedded processors, and collaborating on system-level architecture decisions. You will also contribute to proof-of-concept prototypes, documentation, and support for customer-facing solutions that enhance observability and productivity in EDA workflows. This is a full-time, on-site role based in Mumbai.
Qualifications
Strong foundation in Computer Science and Algorithms, including data structures, algorithmic complexity, and software engineering best practices.
Proficiency in Pattern Recognition and Statistics for building and evaluating robust machine learning models.
Hands-on experience with Neural Networks, including training, optimization, and deployment on resource-constrained or embedded platforms.
Experience with embedded systems development (C/C++), ARM or RISC-V architectures, and performance optimization for real-time applications.
Knowledge of ML frameworks and tools such as PyTorch, TensorFlow, ONNX, and model compression or quantization techniques.
Bachelor’s or Master’s degree in Computer Science, Electrical/Electronics Engineering, or a related field; research or industry experience in embedded ML or EDA is an advantage.
Ability to collaborate in multidisciplinary teams, communicate technical concepts clearly, and take ownership of end-to-end solutions.
Interest in next-generation EDA, FPGA/ASIC design flows, and building globally competitive technology from India.

Work arrangement
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