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Machine learning engineers at Indian product cos and AI startups build the data pipelines, model training infrastructure, and serving systems behind features like Razorpay fraud detection, Swiggy delivery-time predictions, Flipkart product recommendations, and a wave of GenAI products from Indian startups (Sarvam, Krutrim, Yellow.ai, Glance, BharatGPT-adjacent teams). The work spans Python/PyTorch model code, feature stores on Postgres/Feast, GPU training on AWS/GCP, model serving via Triton/vLLM/SageMaker, MLOps tooling (MLflow, Kubeflow, Vertex AI), and the operational glue around RAG/LLM applications. India-specific patterns include US-export ML platform teams (DeepMind India hires, Google IDC AI, Microsoft Azure AI India, Adobe ML India) that overlap 5-9 PM IST, India-fintech fraud models that handle UPI scale (3B+ transactions a month), and a growing layer of Indic-language NLP work at Sarvam, AI4Bharat, and Krutrim. Compensation skews high — strong ML engineers at product cos (Flipkart, Cred, Razorpay, Swiggy) and FAANG India (Google IDC, Microsoft Research India, Adobe ML) routinely clear 70 lakh to 1.5 crore total comp at the senior level.
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