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Roles and Responsibilities:
3 – 5 years of product development experience for large scale systems with high volume and high-performance requirements.
About the Role
AI Engineer with a blend of AI deployment, MLOps, software integration, and AI infrastructure skills, the ideal candidate should have:
Responsibilities
Qualifications
Required Skills
Preferred Skills
Job ID: 147495329
Skills:
text classification , Summarization, Tensorflow, Pytorch, Docker, Python, AWS, Gcp, MLops, Azure, Kubernetes, embeddings, AI workflows, scikit-learn, Hugging Face, reinforcement learning, NLP tasks, workflow automation, semantic search, LangChain, recommendation systems, Transformers, OpenAI, LlamaIndex

Skills:
Retrieval-Augmented Generation (RAG), Sql, Python, Azure, Gcp, Microservices, Tensorflow, Pytorch, AWS, ML Frameworks, Generative AI Concepts, Agentic AI Frameworks, Cloud Platforms, Prompt Engineering, Vector Databases, Pinecone, Weaviate
Skills:
Apis, AI ML, Mssql, Memory Management, MongoDB, FastAPI, Azure, Python, LangChain, Azure Cognitive AI Search, multi-agent orchestration, cloud-hosted AI models, vector databases, prompt engineering, NLP engineering, RAG pipelines
Skills:
Nlp, Deep Learning, Python, Tensorflow, Azure, Machine Learning
Skills:
clay , Tensorflow, AWS, Pytorch, Python, Azure, Gcp, LLMs, Exa, relay.app, Kubeflow, MLflow, scikit-learn, Byword, Hugging Face, vector databases, n8n, AI MLOps workflows, RAG architectures, prompt engineering, multimodal AI systems
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