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Develop embedded compiler features for ML-based edge devices, writing C/C++/Python to power next-gen mobile, IoT, and automotive systems.
Validate and improve Generative AI and Deep Learning models for a large bank, using Python, PyTorch, and cloud platforms to ensure compliance and performance.
Build, deploy, and monitor AI/ML models and MLOps pipelines for federal missions, integrating NLP, LLMs, and predictive analytics into secure enterprise systems.
Lead a team to build and deploy large language model applications, fine-tune models, and create agentic AI systems for mission-critical government use cases.
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.
Principal ML Engineer designs, builds, and deploys production-grade AI systems using LLMs and deep learning, integrating agent workflows across GCP, AWS, and Azure.
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.
Build and deploy AI-powered applications using LLMs, cloud AI services, and GenAI models. Design production-ready pipelines and integrate advanced AI features like chatbots and image processing.
Designs and builds AI-driven applications using cloud AI services, GenAI models, and UX design, ensuring production-ready, scalable systems deployed on cloud or on-prem.
Design and build AI-powered applications using cloud services, generative models, and deep learning. Integrate solutions like chatbots and image processing into production pipelines.
Design and build AI-driven applications using cloud/on-prem pipelines, integrating generative AI models, deep learning, and agentic frameworks like LangChain.
Build and deploy AI/ML systems for government missions, including LLM-powered workflows and agent-based automation in secure environments.
Lead the security architecture for JPMorganChase’s AI/ML platforms, designing controls against threats like prompt injection and data poisoning while guiding secure AI agent development and deployment.
Staff ML Engineer at Zendesk builds and scales AI-powered search solutions (e.g., RAG bots) for customer experience platforms, optimizing retrieval, ranking, and hybrid search (vector + keyword) using LLMs, PyTorch, and cloud infrastructure.
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