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Develops and optimizes AI models for real-time identity verification, facial recognition, and object detection, deploying them across embedded, edge, and cloud systems.
Designs and builds machine learning models to analyze data and improve product performance, working 2 days per week from an HPE office in Bengaluru using Python, TensorFlow, and related tools.
Build and deploy AI-driven compliance automation tools for government clients using Python, ML models, and cloud-native tech in a secure environment.
Build and deploy AI/ML models and data pipelines to tackle public-health, environmental and forensic challenges for New Zealand, using Python/R, MLOps and cloud/Azure tooling.
Design and build AI-driven applications using cloud AI services and generative models, integrating them into production-ready pipelines.
Design and build AI-powered applications using cloud services and generative models, ensuring production-ready quality and integrating deep learning, chatbots, and image processing.
Build production-grade AI systems using ML tools, cloud AI services, and generative models like deep learning and neural networks for enterprise solutions.
Design and build AI-powered applications using cloud services and on-prem pipelines, integrating generative models and deep learning into production systems.
Design and build AI-driven data applications in Snowflake using Cortex AI, Cortex Functions, and Cortex Search for semantic search, LLM-powered transformations, and intelligent data retrieval.
Lead a team to design, build, and ship ML models and LLM/GenAI pipelines for a media-screening platform running on AWS, balancing classical and modern AI approaches.
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.
Design and build AI-powered applications using generative models, deep learning, and cloud/on-prem pipelines to deliver production-ready solutions.
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.
Design and build AI-powered applications and cloud pipelines, integrating generative AI and other models into production-ready systems.
Build and deploy production-grade ML services for a financial-services firm, turning research models into scalable APIs and MLOps pipelines on Azure and GCP.
Build and deploy computer-vision models in Python/PyTorch for real-time situational-awareness systems that run on cloud, edge, and on-premise.
Research and implement machine-learning models for cybersecurity, optimizing them for latency and edge deployment while collaborating with engineers and security teams.
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