AI Systems Engineer

About US

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.

About the Role

We're seeking an AI Systems Engineer who thrives at the intersection of AI model optimization , infrastructure engineering , and applied research .

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.

This is a role for someone who's comfortable navigating ambiguity , researching emerging AI methods , and translating client requirements into robust, production-ready solutions.

You'll work across the full stack—from GPU inference tuning to React-based control dashboards building a resilient and scalable AI delivery platform.

Key Responsibilities -

AI Model Evaluation & Optimization

• Evaluate, benchmark, and optimize AI models (speech, text, vision, multimodal) for latency, throughput, and accuracy.
• Implement advanced inference optimizations using ONNX Runtime , TensorRT , quantization , and GPU batching .
• Continuously research and experiment with the latest AI runtimes , serving frameworks, and model architectures.
• Develop efficient caching and model loading strategies for multi-tenant serving.

AI Infrastructure & Orchestration

DevOps, CI / CD & Automation

Frontend & Developer Tools

Client Interaction & Solutioning

Research & Continuous Innovation

Ambiguous Problem Solving

Required Skills

Nice to Have

Soft Skills

Skills Required

S3, API Design, Bash, Cloudfront, React, Typescript, Javascript, Docker, Terraform, AWS ECS, Load Balancing, Kubernetes, Python