xAI· Model· Palo Alto, CA
Member of Technical Staff - Voice Model
Comp$150,000 – $450,000
Classified Tasks (21)
Automate 0%Augment 86%Human-Only 14%
Augment (18)
AI assists, human decides
Design large-scale speech data curation and processing pipelines
technical
Implement and operate pipelines to collect diverse real-world audio
operational
Generate synthetic audio data for model training
technical
Develop automated annotation workflows for speech datasets
technical
Perform premium audio processing for training and evaluation data
technical
Curate massive speech datasets for training pipeline use
analytical
Pre-train speech-language models at scale
technical
Perform intensive post-training on speech-language models to improve performance
technical
Apply supervised fine-tuning to speech-language models
technical
Apply reinforcement learning and other targeted techniques to enhance models
technical
Optimize models for accuracy, factuality, natural spoken style, conversational tone, and multilingual fluency
technical
Build and iterate a comprehensive evaluation framework for voice models
analytical
Implement and report objective metrics including accuracy, quality, latency, and expressiveness
analytical
Conduct content factuality assessments on model outputs
analytical
Measure and analyze real-time interaction quality in deployed scenarios
analytical
Build experimentation infrastructure (A/B testing) to drive iterative model improvements
technical
Integrate voice models into applications and real-time environments
technical
Ensure stable, low-latency voice experiences across devices and real-time contexts
operational
Human-Only (3)
Requires human judgment
Design and run human preference studies to assess model behavior
analytical
Define spoken interaction specifications in partnership with product teams
communication
Manage the full lifecycle from prototype to global-scale deployment of voice models
leadership
Job description
ABOUT xAI xAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: You will join the Grok Voice Model team to help build the world’s best voice AI. We deliver smooth, natural, low-latency spoken interactions — expressive, multilingual, and reliable across devices and real-time scenarios. We own the full training pipeline: massive data curation, premium audio processing, frontier speech-language pre-training, and intensive post-training to push quality, speed, and stability to the limit. Our goal: make talking to AI feel like conversing with the most charming, kind, and knowledgeable person imaginable. We’re seeking exceptionally smart, execution-oriented engineers to help us get there. RESPONSIBILITIES: Design and execute large-scale speech data curation and processing pipelines, including collection of diverse real-world audio, synthetic data generation, and automated annotation workflows to enable high-quality model training and evaluation. Work on pre-training and post-training of speech-language models, with targeted enhancements through supervised fine-tuning, reinforcement learning, and other techniques to ensure Grok Voice responses are accurate, factually grounded, natural and idiomatic in spoken style, conversational in tone, and fluent across multiple languages. Build and iterate a comprehensive evaluation framework covering objective metrics (accuracy, quality, latency, expressiveness), human preference studies, content factuality assessments, real-time interaction quality, and experimentation infrastructure to measure and improve performance. Work closely with product teams to integrate voice models into applications and real-time environments, define spoken interaction specifications, and handle the full lifecycle from prototype to global-scale deployment for stable, low-latency, delightful voice experiences. BASIC QUALIFICATIONS: Python expert with deep proficiency in writing clean, efficient code for AI/ML systems. Hands-on experience processing large-scale datasets using tools like Spark and Ray for cleaning, augmentation, and feature extraction. Proficiency in pre-training and post-training speech-language models using JAX/PyTorch, including supervised fine-tuning, reinforcement learning, and optimizations for accuracy, factuality, natural spoken style, detail, and multilingual fluency. Ability to set up and run rigorous evaluation pipelines: objective metrics, human preference studies, content factuality checks, and iterative A/B testing to drive model improvements. Experience building or working with large-scale distributed training and inference systems on Kubernetes. Proactive, self-driven attitude — ready to grind in a fast-paced, high-caliber team to deliver outstanding voice AI experiences. </