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Series C AI startup, hybrid India hiring, senior specialized role — moderate candidate competition.
Highly domain-specific ML infrastructure and GPU/inference expertise reduces cross-industry transferability.
Explicit 10+ years, principal-level architecture and ML/GPU infrastructure mandates make filters stringent.
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Lead architecture and technical direction for scalable real-time data processing and ML infrastructure across multiple teams.
Own GPU infrastructure capacity planning, scheduling, and utilization to optimize training and inference costs and latency.
Drive system reliability, observability, and incident response for enterprise production workloads and mentor senior engineers.
10+ years experience building backend and infrastructure systems with architecture ownership at scale.
Deep hands-on experience with large-scale databases, high-throughput messaging systems, and real-time job queues.
Strong experience mentoring senior engineers and making technical decisions through influence.
BTech/MTech/PhD in Computer Science or equivalent; Work Experience Required: 10+ years.
Proven ability to navigate complex codebases and balance architectural tradeoffs in systems you did not originally build.
Track record of driving technical roadmaps and scaling infrastructure predictably through significant company growth or funding stages (Series C or equivalent).
Experience with GPU infrastructure scaling, ML model inference optimization, distributed messaging, and platforms like Django, Celery, Redis, PostgreSQL, and Google Cloud is highly valued.