Shreya Gupta stands as a distinguished Senior Software Engineer and a visionary AI/ML specialist, renowned for her instrumental role in designing, architecting, and deploying advanced, highly scalable systems that power the next generation of artificial intelligence at globally recognized industry titans including Google, Goldman Sachs, and Expedia Group. With a profound and demonstrable expertise in the intricate domains of machine learning scheduling systems, innovative resource optimization algorithms, and the creation of sophisticated unified infrastructure solutions, Shreya has consistently driven significant enhancements in the efficiency of AI model training pipelines while delivering substantial reductions in operational costs and computational overhead.

Her impactful work spans the full spectrum of high-performance AI models, from the complex demands of cutting-edge Large Language Models (LLMs) that are reshaping human-computer interaction, to the rigorous requirements of deep learning systems that underpin breakthroughs in various scientific and commercial fields. Shreya has been a pivotal leader and core technical architect on transformative, high-stakes projects such as Google's Gemini 2.0, contributing to the advanced scheduling infrastructure essential for its multi-modal AI training at unprecedented scale, and Project Janus (ML Capacity Unification), where she pioneered a unified scheduling layer to intelligently share heterogeneous AI workloads across Google's vast External (GCE) and Internal (TI) domains. This groundbreaking initiative directly tackled critical inefficiencies, unlocking thousands of previously underutilized high-end GPUs, demonstrably improving fleet efficiency by over 30%, and realizing hundreds of millions of dollars in compute cost savings. Furthermore, her innovations have been instrumental in advancing sustainable AI practices by significantly reducing idle TPU cycles and lowering the overall carbon footprint of large-scale AI operations. These achievements have firmly solidified her reputation as an influential leader and a key innovator within the competitive tech industry.

Shreya's exceptional technical prowess and strategic foresight are powerfully complemented by an unwavering passion for mentorship and a commitment to fostering vibrant, innovative technical communities. Her leadership extends beyond project execution to inspiring and guiding fellow engineers, actively contributing to a culture of continuous learning and technological advancement. This dedication to impact and excellence has been recognized through numerous prestigious accolades, including the Google Tech Impact Award (2024) for her significant contributions to driving sustainable AI initiatives and delivering high-impact technical solutions, the Google Perfy Award for optimizing key performance metrics in critical projects, and her notable recognition as one of the Top 50 Women Coders in India by LinkedIn (Nov 2017).

Throughout her distinguished career, Shreya has consistently demonstrated a unique ability to bridge the gap between cutting-edge, often theoretical, academic research and its pragmatic, real-world implementation. She excels at translating complex AI/ML concepts into tangible, scalable, and transformative solutions that deliver measurable business impact and solve critical operational challenges. Academically distinguished, Shreya holds a Master’s in Computer Science (Honors) from the University of Southern California, where she was a Merit Holder for Academic Excellence, and a Bachelor’s in Computer Science from Indira Gandhi Delhi Technical University for Women, India, from which she graduated as a University Topper and Valedictorian, earning both the Chancellor and Vice Chancellor Gold Medals. This strong academic foundation, combined with her extensive industry experience and visionary leadership, positions Shreya Gupta as a recognized and influential figure in the field, continually striving to create sustainable, high-impact solutions that push the boundaries of artificial intelligence and machine learning for a more intelligent and efficient future.