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Build production-grade AI systems using ML tools, cloud AI services, and generative models like deep learning and neural networks for enterprise solutions.
Build and deploy NLP, deep learning, and RAG models to automate financial analytics workflows, integrating data pipelines and cloud MLOps on AWS.
Design and architect large language models (LLMs) to process and generate natural language, training on vast unlabeled text datasets and refining model performance.
Build and deploy AI-driven applications using generative models, deep learning, and cloud AI services. Design production-ready pipelines and integrate AI into systems.
Build and deploy AI-driven applications using cloud AI services, generative models, and deep learning frameworks like TensorFlow or PyTorch.
Build AI-powered applications and cloud pipelines using GenAI, deep learning, and neural networks, ensuring production-ready quality and collaborating across teams.
Build production-ready AI systems using cloud AI services, generative models, and deep learning frameworks like TensorFlow or PyTorch.
Build production-grade AI systems using cloud AI services, generative models, and deep learning frameworks like TensorFlow or PyTorch to solve complex business problems.
Build and maintain the iOS app for an AI-native assistant, integrating SwiftUI, Swift, and on-device ML to deliver responsive, reliable AI interactions.
Build and maintain a Kotlin-based Android app where AI-powered features like chat and vision are core to the user experience, focusing on performance and reliability.
Research and implement machine-learning models for cybersecurity, optimizing them for latency and edge deployment while collaborating with engineers and security teams.
Build statistical and ML models for healthcare analytics and pharma marketing mix modeling to optimize spend and strategy using Python, SQL, and cloud tools.
Build and deploy AI/ML models for healthcare claims processing using PyTorch/TensorFlow, MLOps pipelines, and cloud tools to reduce payment inaccuracies and waste.
Build, deploy, and monitor AI/ML models and MLOps pipelines for federal missions, integrating NLP, LLMs, and predictive analytics into secure enterprise systems.
Design and deploy cutting-edge AI/ML models, including LLMs and SLMs, to power next-gen customer-facing and operational solutions at Cisco’s CX AI Incubation team.
Build and deploy production-grade AI services and integrations in Python, integrating models into enterprise systems like ERP/CRM and ensuring scalable, secure AI adoption.
Develop and optimize computer-vision algorithms into production-ready C++/Python code for embedded and mobile devices, focusing on performance and power constraints.
Principal ML Engineer designs, builds, and deploys production-grade AI systems using LLMs and deep learning, integrating agent workflows across GCP, AWS, and Azure.
Lead a team building generative AI and agentic systems for healthcare, including LLMs, RAG, and AI agents, from prototyping to production with MLOps and Responsible AI practices.
Build and deploy AI-powered applications using LLMs, cloud AI services, and deep learning frameworks like TensorFlow or PyTorch.
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