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Tier-1 brand and metro location increase competition, but senior and specialized role moderates density.
Role requires deep LLM, MLOps, and infra expertise, making candidates less transferable across unrelated industries.
Explicit 8-12 years requirement plus many mandatory ML/LLM, MLOps, and infrastructure skills makes filtering strict.
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Lead and shape AI/ML initiatives within the organization, focusing on advanced AI and machine learning implementations.
Develop, deploy, and optimize large language model (LLM) infrastructure and services using technologies like Python, FastAPI, and container orchestration (Kubernetes).
Manage end-to-end AI/ML lifecycle including model development, MLOps, feature engineering, and deployment with measurable impact on business decision-making and client outcomes.
8-12 years of professional experience with at least 4 years in AI/ML or a related field.
Bachelor's degree in Engineering (B.Tech) is mandatory; M.Tech/MCA/MBA considered preferred.
Strong technical skills in Python, LLM frameworks (Hugging Face Transformers, LangChain), big data processing (Spark), and microservices architecture.
Experience in MLOps, DevOps tools (Terraform, Jenkins, GitHub Actions), containerization (Docker, Kubernetes), version control (Git), and cloud platforms (AWS, GCP, Azure).
Senior technical leader with deep expertise in AI/ML, especially in LLM development, optimization, and deployment at scale.
Experienced in designing and implementing scalable, microservices-based AI platforms optimized for performance, including expertise in MLOps and DevOps integration.
Strong background in experimental design and statistical analysis relevant to AI model validation and fine-tuning, suited for advisory roles in data-driven client solutions.