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Design and fine-tune large language models to improve natural language understanding and generation for domain-specific tasks.
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.
Design and tune large language model architectures, optimizing neural networks for natural language processing tasks using vast unlabeled text datasets.
Design and optimize neural network architectures for large language models that process and generate human-like text, using machine learning frameworks.
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.
Design and architect large language models (LLMs) that process and generate human-like text, focusing on neural network configurations and large-scale data handling.
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.
Design and architect large language models for natural language processing, refining neural network parameters and collaborating with teams to integrate models into applications.
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-powered applications using cloud services and generative models, with a focus on production-grade ML pipelines and deep learning techniques.
Design and build AI-powered applications using LLMs, deep learning, and cloud services, deploying production-ready solutions with a focus on generative AI and neural networks.
Engineer capacity and capital plans for a semiconductor fab using AI-driven analytics and industrial engineering to optimize production loading, scenario analysis, and capex forecasting.
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