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Specialized GenAI role but mid-level and metro hiring increases applicant density.
Core ML/GenAI skills transfer across sectors, yielding low background sensitivity.
Multiple mandatory AI/ML, GenAI, cloud, and MLOps requirements plus explicit 2–5 years experience.
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Design, build, and deploy AI/ML models including Generative AI and RAG pipelines for real-world business applications.
Develop and optimize scalable AI solutions using Azure AI or equivalent cloud platforms focusing on performance and cost efficiency.
Implement Agentic AI workflows for automation and multi-step task execution while collaborating with cross-functional teams.
Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or related field.
2–5 years of professional experience in AI/ML development.
Proficient in Python and AI/ML frameworks (PyTorch/TensorFlow, LangChain, Transformers) and experience with Generative AI techniques.
Hands-on experience with Azure AI or other cloud AI services, including model deployment and MLOps tools like MLflow, Docker, Kubernetes.
Experienced AI/ML developer with practical knowledge of LLMs, embedding techniques, and prompt engineering for GenAI solutions.
Skilled in building RAG pipelines using vector databases and implementing Agentic AI frameworks for task automation.
Comfortable working in cloud-native environments with CI/CD integration and optimizing AI models for scalability and efficiency.