Senior Machine Learning Engineer, Voice AI

Highlights

• Own the serving stack powering real-time voice agents at production scale.
• Shape the shift from pipeline voice apps to end-to-end speech-to-speech.
• Join a small early-stage team with outsized product impact.

What they offer

• startup equity
• health insurance

Ideal candidate

A product-minded ML engineer with 5+ years shipping production inference systems who thrives on small, fast teams and obsesses over latency, reliability, and developer experience for real-time voice.

Requirements

• 5+ years of experience in ML engineering, with a focus on model serving, inference optimization, or ML infrastructure.
• Hands-on experience with LLM serving engines (vLLM, SGLang, TensorRT-LLM, or similar) — comfortable reading and modifying engine internals, not just using APIs.
• Strong proficiency in Python and PyTorch; experience with GPU profiling and optimization (CUDA, memory management, kernel-level debugging).
• Track record of shipping ML systems to production with measurable performance improvements.
• Strong product sense — you think about what developers building voice apps actually need, not just what's technically interesting.
• Comfort working on a small, early-stage team where you'll wear multiple hats and move fast.
• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field, or equivalent practical experience