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Mid-level ML role in Bangalore with a common 3-5 year band and metro pull increases competition moderately.
Requires specialized ML/LLM systems experience, making cross-industry transfers difficult.
Explicit 3-5 years plus mandatory LLM, inference and production ML skills create stringent shortlisting filters.
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Own and reduce the cost per interaction of LLM-based AI platform from 40 to 2 within 6 months while maintaining performance.
Optimize cloud infrastructure spending, reducing monthly costs from 20L to 4L by balancing latency, throughput, and cost across Azure and compute layers.
Build continuous fine-tuning and learning pipelines that improve model performance and platform intelligence with each customer deployment, enabling new AI-native product categories.
3-5 years of experience in machine learning, applied AI, or systems engineering.
Experience with LLMs, production ML systems, and inference optimization.
Location: Bangalore, working Monday to Friday, 5 days a week.
Not explicitly mentioned: specific degree requirements or notice period.
Hands-on expertise in LLM optimization techniques such as prompting, fine-tuning, distillation, and cost-performance trade-offs.
Experience building scalable, high-performance ML systems with demonstrable cost reduction and performance improvement outcomes.
Strong systems thinking with focus on real-world impact, integrating infrastructure optimizations, caching strategies and model routing for defensible ML advantages.