Posted:1 day ago|
Platform:
On-site
Full Time
Shunya Labs is building the Voice AI Infrastructure Layer for Enterprises powering speech intelligence, conversational agents, and domain-specific voice applications across industries. Born from deep work in mental-health AI and built for global enterprise scale, our stack combines state-of-the-art ASR/TTS models with an open-weights philosophy , driving accuracy, privacy, and scalability.
You will evaluate, host, and optimize a wide range of AI models—spanning ASR, LLMs, and multimodal systems and build the orchestration layer that powers scalable, low-latency deployments.
You’ll work across the full stack—from GPU inference tuning to React-based control dashboards building a resilient and scalable AI delivery platform.
· Evaluate, benchmark, and optimize AI models (speech, text, vision, multimodal) for latency, throughput, and accuracy.
· Develop efficient caching and model loading strategies for multi-tenant serving.
· Implement observability and monitoring (Prometheus, Grafana, CloudWatch) across the model-serving ecosystem.
· Build intuitive internal tools for model comparison, experiment management, and deployment control.
· Prototype quickly, iterate with feedback, and deliver robust production systems.
· Evaluate emerging frameworks for model serving, fine-tuning, and retrieval (LangChain, LlamaIndex, GraphRAG, etc.).
· Proactively identify and implement performance or cost improvements in the model serving stack.
· Share learnings and contribute to the internal AI knowledge base.
· Break down high-level goals into actionable technical strategies.
· Balance trade-offs between accuracy, latency, and cost while innovating under uncertainty.
· Excellent problem-solving in ambiguous, evolving environments.
· Strong ability to research, self-learn, and prototype emerging AI technologies.
· Confident communicator who can translate technical findings to business impact.
· Ownership mindset with a collaborative, solution-oriented approach.
Shunya Labs
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