Himanshu Lal

About Himanshu Lal

As an accomplished Machine Learning Engineer with over six years of experience, I specialize in building scalable, efficient, and innovative AI solutions that bridge the gap between cutting-edge research and real-world implementation. My journey has been defined by a passion for creating impactful systems and mentoring teams to adopt best practices in machine learning and data science. At AiDash, I spearheaded the development of the Vyom Platform, integrating Kubeflow to revolutionize ML workflows with automated pipelines for training, deployment, and monitoring. My contributions include designing the HILO system for continuous model monitoring and retraining, which significantly enhanced the platform\'s scalability. These efforts reduced pipeline complexities to mere lines of code and cut training time by 60%, demonstrating my ability to deliver performance-driven solutions. My experience extends to Intel, where I optimized ML/DL workflows and improved inference times by leveraging advanced quantization techniques. At Accenture, I developed AI solutions (Assembly & Cosmetic Inspection, AutoML) for Defect Detection and video Object Tracking, utilizing cutting-edge Deep Learning models and Google Cloud technologies. I also spearheaded blockchain innovations, contributing to the Hyperledger Bevel project under the Linux Foundation, reducing deployment times for DLT platforms.Currently, my academic research focuses on distributed training, model optimization techniques (quantization, pruning, fine-tuning), and inference optimization for large language models. These projects reflect my commitment to staying ahead of advancements in machine learning and artificial intelligence. Beyond my technical expertise, I am deeply invested in fostering collaboration and mentorship. I’ve conducted technical enablement sessions, trained teams on AI frameworks, and guided organizations in adopting scalable ML platforms. I thrive at the intersection of technical innovation and impactful leadership. I am eager to continue driving transformative AI solutions, mentoring teams, and contributing to initiatives that shape the future of machine learning. Committed to staying at the forefront of AI advancements, exploring emerging technologies like Gen AI and Stable Diffusion Models.Let’s connect to discuss how we can leverage AI and data-driven strategies to create meaningful outcomes.

Experience

1. Sr Data Scientist

   高通

   Aug 2025 — Present · San Diego, CA, US

   AI Systems Engineer specialized in deploying high-throughput inference stacks and modular AI architectures.Hardware Acceleration: Developing custom inference SDKs and BYOM pipelines for Qualcomm® AI200/250 Data Center platform, focusing on efficient transformers serving and disaggregated architectures.Enterprise Orchestration: Building Depend AI Platform, an enterprise-grade engine featuring a modular plugin architecture to automate complex codebase analysis, indexing, documentation, and dependency mapping.Automated Intelligence: Engineered an end-to-end Order Processing system integrating OCR and context-aware validation with human-in-the-loop feedback cycles for continuous model optimization.

Education

• Maulana Azad National Institute of Technology

  Bachelor's degree, Computer Science

• University of Arizona

  Master's degree, Information Science : Machine Learning

• St Francis Convent Sn. Sec. School

  AISSCE