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Showing 10 jobs
Skills:
Tensorflow, Azure ML, Pytorch, Docker, Kubernetes, Python, AWS, RNNs, LLMs, Scikit-learn, MLflow, deep learning architectures, CNNs, prompt engineering, SageMaker, GCP Vertex AI, Kubeflow, Transformers, MLOps tools
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine
Skills:
Power Automate, Pyspark, Sql, Databricks, Azure deployment, Power Apps, Autogen-based architectures, Azure AI Foundry, prompt engineering, Azure AI services, Microsoft Fabric, OpenAI, Azure Cognitive Services, Copilot Studio
Skills:
Machine Learning, MLops, Azure, Summarization, Python, Entity Extraction, LLMops, NLP Techniques, Model Training, Arize, Fine-Tuning, Agentic AI, Classification, Langfuse, RAG Prompt Optimization, LLMOps Platforms
Skills:
data engineering , Java, Node.js, Azure ML, Gcp, Azure, Python, AWS, LangChain, Generative AI, data pipelines, LLMs, Hugging Face Transformers, MLflow, embedding models, vector databases, Vertex AI, Kubeflow, Transformers, Diffusion models, RAG pipelines, ETL workflows
Skills:
Git, Azure Functions, Python Programming, FastAPI, MongoDB, Kubernetes, agentic AI solutions, traditional AI algorithms, DevOps practices, AI development workflows, Redis Cache, vector databases, Jupyter Notebook, Relational Databases, ADLS, Azure services, CI CD pipelines, Generative AI LLMs
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine
Skills:
Machine Learning, Nlp, Pytorch, Cloud Technology, MLops, Python, AWS, Generative AI, Prompt engineering, Distributed training pipelines, Langchain, scikit-learn, LLMOps, Ai, Guardrails, LangGraph, LLM evaluation methodologies, LLM Agentic workflows, LLM technologies, Voice Conversational AI, LlamaIndex, Transformer architectures
Skills:
BigQuery, Python, Cloud Functions, GenAI APIs, Vertex AI, Google Kubernetes Engine
Skills:
Python, LangChain, AI Agents, Vector databases, LangFlow, AI memory frameworks, Agentic AI systems, Generative AI architectures, LangGraph, semantic search, Tool calling frameworks, Embedding models, MCP Server implementation, Function calling, Memory sharing architectures, RAG pipelines, Multi-agent orchestration
