Sr. Model Engineer, Voice

xAI•Palo Alto, CA

About The Position

You'll join the Grok Voice Model team as a software engineer, designing, building, and operating the software systems behind Grok Voice. The product delivers natural, low-latency, multilingual spoken interactions across devices and in real time. The team owns the full engineering stack behind the model, from large-scale data processing and distributed training to production deployment.

Requirements

  • Bachelor's degree in computer science, software engineering, computer engineering, electrical engineering, or another engineering discipline.
  • Experience writing production-quality code in Python, PyTorch, JAX, Rust, or C++.
  • At least 2 years of experience working with large-scale voice-related products.

Nice To Haves

  • Experience building and running large-scale distributed training and inference systems on Kubernetes.
  • Expert-level Python skills, including writing clean, efficient, production-quality code for large-scale systems.
  • Experience implementing and optimizing model training and inference software in JAX or PyTorch.
  • Experience building automated testing, evaluation, and A/B experimentation pipelines for production systems.
  • Hands-on experience building distributed data processing systems with tools such as Spark and Ray.
  • A proactive, self-driven attitude and the ability to deliver in a fast-paced, high-caliber team.

Responsibilities

  • Design, build, and maintain large-scale distributed data pipelines that ingest, process, and annotate real-world and synthetic audio for training and evaluation.
  • Build and optimize distributed training infrastructure and software for speech-language models in JAX and PyTorch, including systems for supervised fine-tuning and reinforcement learning at scale.
  • Build automated evaluation and testing systems to measure accuracy, audio quality, latency, and real-time performance, as well as experimentation infrastructure for validating model releases.
  • Integrate voice models into production applications and real-time services; write technical specifications for spoken interactions; and own deployment from prototype to global scale, emphasizing stability, low latency, and reliability.
  • Profile and optimize system performance across training and inference, including throughput, latency, memory use, and compute efficiency.

Benefits

  • Equity
  • Comprehensive medical coverage
  • Vision coverage
  • Dental coverage
  • Access to a 401(k) retirement plan
  • Short- and long-term disability insurance
  • Life insurance
  • Various other discounts and perks
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