Niranjan Wartikar — Director of Engineering

With close to 30 years of industry experience covering both hardware and software, in the semiconductor, computer and consumer electronics industry, I have donned many hats leading product strategy, product development and product delivery for a variety of B2C and B2B products. Currently, at NVIDIA, I lead global and multi-disciplinary software teams, that cover a variety of technology areas involving Generative AI (LLM, RAG, Agents), Conversational AI (Speech Models and frameworks), Audio/Multimedia user and kernel space software and DSP firmware. With my teams, I help drive product roadmaps and their execution to achieve world class outcomes, in turn, helping drive growth for my organization, across various business areas covering enterprises, developers and end consumers. I am passionate about building end-to-end products that are either deployed on Cloud, Edge or released as Embedded and End-consumer products. What drives me is that these products can help solve real world problems that improve efficiency and productivity for enterprises, enrich consumers with never-seen/heard experiences, and most importantly make the world a better place in various aspects. The fact that my work covers a broad expanse of the entire product life cycle, ranging from chips, to platforms, to software, to end products, gives me an opportunity to look at problems and their solutions end-to-end, and help create wider impact. I’m equally interested in building teams and leaders, who demonstrate passion for high performance and agility, but also honor inclusion, diversity and respect for each other. With the Generative AI age catching up, I am all for seeing a world that harmonizes human intelligence and Responsible AI, to help improve human lives, in all strata of our society. Following are the work areas that I lead at NVIDIA to drive my mission and passion: - NVIDIA RIVA Speech AI Inference and Training for Speech Models that cover ASR, TTS, Translation etc. - Conversational AI Speech to Speech Pipelines for Digital Human Tech, and other areas - MLOPS lifecycle to develop AI models and make them available as Ready-to-deploy microservices in the form of NIM (NVIDIA Inference Microservice) - NIM Blueprints and Agents, that help solve enterprise problems using a variety of NIMs - RAG (Retrieval Augmented Generation) for developers and enterprises - LLM Model Development around small language models (SLM) and Sovereign AI initiatives - Audio drivers for Tegra SOCs and their Jetson and Drive platforms - Full stack Android Audio solutions for NVIDIA Shield and Auto platforms

Stackforce AI infers this person is a leader in AI and Consumer Electronics, specializing in product strategy and development.

Location: Pune, Maharashtra, India

Experience: 31 yrs 7 mos