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Builds full-stack cybersecurity tools and AI-powered solutions using cloud platforms (AWS/Azure/GCP), modern frameworks, and secure development practices.
Lead AI engineering at Deloitte, setting vision and standards for GenAI and agentic systems integrated into enterprise products while coding, mentoring teams, and driving cost-aware, secure, and scalable AI solutions.
Lead engineering vision for Deloitte’s Applied AI platforms, designing GenAI and agentic capabilities into enterprise products while coding, mentoring teams, and setting standards for scalable, secure AI systems.
Senior consultant building and deploying AI-enabled cybersecurity solutions for clients, leading engineering teams, and shaping technical proposals with hands-on full-stack development.
Lead engineering vision for Deloitte’s Applied AI products, defining GenAI and agentic capabilities, setting standards, and coding while mentoring teams to deliver scalable AI solutions.
Lead engineering vision for Deloitte’s Applied AI products, defining GenAI and agentic capabilities, setting standards, and coding while mentoring teams to deliver scalable, secure AI solutions.
Develop secure, AI-powered back-end services for cybersecurity solutions using Python, Java, Go, and cloud tools like GCP and Kubernetes.
Senior Software Engineer at Seyond in Sunnyvale, CA, developing LiDAR-based perception software and machine learning models for autonomous driving and smart infrastructure using edge AI platforms like NVIDIA Jetson.
Designs AI-driven data pipelines and statistical models to discover drug candidates, integrating biological and chemical data while collaborating with cross-functional teams.
Build and deploy AI/ML models (NLP, deep learning) using Python and frameworks like TensorFlow/PyTorch, migrating SQL Server reports to a Snowflake data lake.
Leads advanced data-science projects to build and deploy ML models that optimize Walmart’s supply-chain strategy, using Python/SQL and collaborating with cross-functional teams to translate data into business impact.
Build ML models and NLP pipelines to analyze real-estate data, predict borrower risk, and guide lending decisions using Python libraries like PyTorch and TensorFlow.
Build and deploy computer vision and generative AI models for retail applications like visual search, personalized recommendations, and fraud detection using PyTorch, diffusion models, and multimodal systems.
Builds ML models to extract clinical insights from wearable sensor data, collaborating with customers to validate algorithms and improve digital health outcomes.
Builds ML models to extract clinical insights from wearable sensor data, focusing on time-series analysis and digital health applications.
Build and deploy ML models end-to-end: train, optimize, and package solutions while setting up MLOps pipelines, monitoring, and data governance for production AI systems.
Build and deploy AI/ML models (LLMs, NLP, vision, recommender systems) as scalable microservices, working with cloud partners and business teams to drive data-driven decisions.
Lead the design and delivery of LLM-powered AI workflows for JPMorganChase’s employee platforms, integrating agentic AI and MCP tools to improve productivity and operational efficiency.
Build and deploy AI/ML models, NLP, and LLM solutions to extract insights from unstructured data and support business decisions using Python, cloud platforms, and vector databases.
Lead the design and deployment of ML models for credit risk, collections, fraud detection, and customer segmentation in digital lending, using Python, SQL, and MLOps tools.
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