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Build and scale core ML infrastructure and systems, turning research models into production-ready services while ensuring reliability and performance for user-facing AI features.
Principal Data Scientist at Walmart leading end-to-end AI system design, autonomous agent development, and production ML deployments using PyTorch, LangChain, and multi-cloud platforms.
Lead a team building secure Python solutions (APIs, microservices) using cloud/DevOps tools, AI-driven threat modeling, and secure coding practices to protect JPMorganChase systems.
Build and deploy AI-powered web apps and APIs for smart manufacturing, integrating LLMs, robotics, and predictive models to optimize Micron’s global semiconductor production lines.
Design and optimize FPGA-based signal processing and embedded computing solutions for defense and aerospace, using RTL, DSP Builder, and embedded processors.
Develop next-gen CT scanner software, implementing deep-learning image reconstruction algorithms and optimizing them for GPU/Linux using C++ and CUDA.
Build and deploy production-grade AI systems, including LLM-powered agents and analytics, to enhance customer experience and workforce productivity using NLP, retrieval-augmented generation, and agentic workflows.
Build and deploy production-grade AI agents using LLMs, RAG, and orchestration frameworks to power Workday’s next-gen HR platform at global scale.
Own AI and analytics product strategy for Motorola’s Avigilon platform, turning cutting-edge computer vision and generative AI into scalable security solutions that protect people and places.
Lead enterprise Generative AI strategy, designing advanced RAG architectures and evaluation frameworks to deploy production-grade LLM systems with a focus on accuracy, safety, and business impact.
Build and scale AI/ML systems, models, and infrastructure for a cloud communications platform, including generative AI, NLP, and MLOps pipelines.
Lead a team building enterprise-scale banking applications with Java/Spring Boot and React, while integrating generative AI models (LLMs, etc.) into Citi’s systems.
Builds Python-based AI tools for meteorology/oceanography projects, using LLMs and Docker, while supporting government systems at Stennis Space Center.
Build and optimize Neuron, AWS’s ML compiler/runtime for training GenAI models on Trainium chips, tuning parallelism and kernels across PyTorch/JAX to maximize throughput.
Build and fine-tune generative AI models and agentic systems to improve AWS services and customer experiences using deep learning and reinforcement learning.
Principal Data Scientist at AWS leading multi-year AI/ML analytics strategy to drive product growth across Compute, GenAI, Database, and Storage services.
Lead AI initiatives for drug discovery and clinical operations, designing and deploying generative AI, RAG systems, and agentic workflows while managing contractors and ensuring responsible, production-ready AI systems.
Lead AI initiatives for drug discovery and clinical operations, designing generative AI systems, RAG pipelines, and agentic workflows to accelerate research and development in a regulated healthcare environment.
Build and maintain large-scale HPC/AI clusters, automate deployments with IaC and CI/CD, and optimize GPU computing workflows for NVIDIA’s cutting-edge systems.
Own the AI inference performance roadmap at NVIDIA, turning deep optimization techniques into products that improve latency, efficiency, and cost per token across the inference stack for LLM deployments.
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