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Mid-level ML role, broad GenAI/LLM skills and metro hiring make standing out highly competitive.
Role requires specialized ML/LLM and data engineering expertise, limiting cross-industry transferability.
Explicit 5+ years and extensive mandatory ML, cloud, LLM and data engineering requirements increases filter strictness.
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Own end-to-end implementation and maintenance of complex AI/ML and data solutions for clients, including data preprocessing, model deployment, and performance monitoring.
Collaborate closely with business stakeholders, clients, data scientists, software engineers, and DevOps teams to align AI/ML initiatives with client needs and product capabilities.
Evaluate and integrate new machine learning technologies and tools to enhance solution scalability, maintainability, and reliability.
Bachelor’s or Master’s degree in Computer Science, Information Technology or related field (e.g., B.Tech, MCA, MS Computers).
Minimum 5 years of experience in AI/ML implementation, data and software development.
Proficiency in Python programming and hands-on experience with AI/ML frameworks including TensorFlow, PyTorch, scikit-learn.
Experience with cloud platforms such as AWS and Microsoft Azure, and exposure to related DevOps tools (Docker, Databricks).
Experienced in end-to-end AI/ML solution delivery with strong integration and deployment skills across diverse client data environments.
Familiar with advanced NLP, Gen AI, and LLM technologies including LangChain, HuggingFace, and relevant APIs.
Skilled in building scalable data infrastructure pipelines and monitoring systems integrating visualization tools like Power BI or similar.