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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.
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.
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.
Develops backend software for digital pathology image analysis, optimizing rendering and workflows using C++/Python and OpenGL/Qt.
Lead image-quality development for GE Healthcare’s CT scanners, defining metrics, optimizing reconstruction algorithms, and guiding cross-functional teams to improve clinical image fidelity.
Lead architecture and optimization of high-performance CT image reconstruction pipelines using C++/CUDA, parallel computing, and AI/ML for next-gen medical imaging products.
Senior AI Engineer builds and operationalizes GenAI and ML solutions on GCP/Vertex AI, deploys agentic platforms, and maintains production pipelines with strong Python and cloud engineering skills.
Builds and automates AI/ML pipelines in Python and cloud platforms (GCP preferred), deploys GenAI models, and maintains production-grade ML workflows.
Design and implement AI/ML systems, including GenAI models and neural networks, to build production-ready applications and pipelines.
Build and deploy AI-powered applications using LLMs, cloud AI services, and deep learning frameworks like TensorFlow or PyTorch.
Build and deploy AI systems using Generative AI, LLMs, and deep learning; design cloud or on-prem pipelines and integrate AI models into production applications.
Design and build AI-driven applications using generative models, deep learning, and cloud/on-prem pipelines. Integrate LLMs, RAG, and vector databases to create production-ready solutions.
Build and deploy AI-powered applications using generative models, cloud AI services, and deep learning frameworks like TensorFlow or PyTorch.
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