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Tier-1 brand, metro location, mid-level generalist ML role with broad GenAI skillset increases competition.
Role requires specialized LLM, MLOps, and infra expertise, limiting cross-industry transferability.
Multiple mandatory GenAI, MLOps, cloud and infra skills plus explicit 4-8 years requirement make shortlisting highly strict.
Design, develop, and lead AI/ML initiatives focusing on large language models (LLMs) and big data processing.
Develop and deploy data pipelines and AI/ML models in microservices architecture using Python, with expertise in LLM frameworks and MLOps.
Manage end-to-end AI/ML lifecycle including feature engineering, model fine-tuning, deployment, and optimization on cloud platforms with infrastructure as code and container orchestration.
4+ years of relevant experience in AI/ML or related field.
Strong proficiency in Python and experience with LLM frameworks like Hugging Face Transformers and LangChain.
Experience with microservices architecture, container orchestration (Kubernetes), Terraform/CloudFormation, Git, MLflow, and cloud platforms (AWS/GCP/Azure).
Bachelor's or Master's degree in Engineering (B.Tech/M.Tech) or MCA/MBA.
Experienced in developing and optimizing large-scale LLM systems including chatbot, recommendation, and semantic search applications.
Proficient in MLOps practices for continuous model deployment, monitoring, and retraining in cloud environments.
Strong background in software engineering with knowledge of distributed systems, microservices, DevOps automation, and advanced AI/ML lifecycle management.