2 months ago
Bengaluru, IndiaStaff+
Responsibilities
- Own the architecture and technical direction for high-throughput real-time data processing and distributed messaging systems.
- Define and execute the ML platform roadmap for model training and serving infrastructure.
- Lead GPU capacity planning, scheduling, utilization, burst handling, and cost management across training and inference fleets.
- Scale model inference through batching, routing, quantization, compilation, autoscaling, and caching while maintaining output quality.
- Drive uptime, observability, and incident response for production serving systems.
- Translate ambiguous business problems into executable technical plans and coordinate cross-functional initiatives.
- Lead design reviews, mentor senior engineers, and establish engineering standards across teams.
- Evaluate emerging tools and techniques and adopt them when their complexity is justified.
Requirements
- 10+ years building backend and infrastructure systems with ownership of architecture and design at scale.
- Deep hands-on experience with large-scale databases, high-throughput messaging systems, and real-time job queues.
- Ability to navigate complex codebases and reason about architectural tradeoffs in systems the candidate did not build.
- Experience mentoring senior engineers and driving technical decisions through influence rather than authority.
- Strong written communication for technical and executive audiences across time zones.
- BTech, MTech, or PhD in Computer Science, or equivalent experience.
- Bonus: production experience with Django, Celery, Redis, PostgreSQL, and Google Cloud.
- Bonus: hands-on experience scaling GPU infrastructure and model inference in production, including capacity planning, scheduling, autoscaling, and latency and cost optimization.
- Bonus: experience with vLLM, TensorRT, Triton, Ray Serve, or equivalent inference tooling.
- Bonus: experience scaling a platform through a comparable growth stage or at a global product company’s India site.
- Bonus: background in speech, NLP, or information retrieval systems.
Benefits
- Health coverage for the employee, spouse, children, and parents.
- Real ownership over systems used by enterprises worldwide and autonomy over how they are built.
- The role is based in Noida or Bengaluru and involves collaboration across India and US-based teams; the hiring process typically takes 2 weeks across 4 stages.
Tech Stack
Categories
About Level AI
Level AI builds a conversational intelligence platform for enterprise contact centers, combining speech AI, NLP, and retrieval to analyze customer interactions and drive QA, coaching, automation, and analytics. It sells its software to large customer service and sales teams, typically via subscription. Founded in 2018 and headquartered in Mountain View, the company is Series C–funded, with customers such as Wayfair, Smartsheet, Chime, Gusto, and Swiss Re.