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Tier-1 brand and Bengaluru metro increase competition, but specialized ML/LLM seniority limits candidate pool.
Specialized LLM inference, GPU programming, and distributed ML systems make candidate transferability low.
Explicit 9+ years, manager requirement, and many mandatory ML infra and GPU skills create strict filtering.
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Lead and grow AI engineering teams with full ownership of execution and delivery.
Architect and scale Meesho's AI platform including cross-region model inference, multi-GPU fleet management, distributed training, and feature-engineering infrastructure.
Drive end-to-end inference and model optimization at both the model and system level to support production-grade AI use cases impacting millions of users.
Bachelor's or Master's degree in Computer Science or related field.
9+ years of software engineering experience including at least 2 years in managing engineering teams.
Hands-on experience with modern LLM inference stacks and production low-latency model serving at scale.
Experience with distributed training frameworks (e.g. PyTorch FSDP, DeepSpeed), GPU fleet management (Kubernetes/GKE), and proficiency in Python and performance-critical languages (C++, Go, Rust).
Experienced in building and scaling high-scale AI platforms for consumer products with millions of users.
Strong technical leadership in GPU/ CUDA programming, inference optimization including quantization and kernel tuning, and ML infrastructure (MLOps, LLMOps).
Skilled in managing multi-region, multi-cluster GPU deployments and driving cost efficiency and reliability of large GPU fleets in production.