Added 2 Nov 2026 · Engineering
Job description
SpaceX was founded under the belief that a future where humanity is out exploring the stars is fundamentally more exciting than one where we are not. Today, SpaceX is actively developing the technologies to make this possible, with the ultimate goal of making life multiplanetary and expanding consciousness to the stars.
SpaceXSI is building Super Intelligence to help humanity understand the universe. Our teams are building the full Super Intelligence stack: from our Colossus supercomputers, to Grok models, to our suite of applications, including Grok Bot, Grok Build, Grok Imagine, Grok Voice, and X. We're creating a powerful flywheel where more compute trains better models, better models power more useful products, and what we learn from people using those products shapes what we build next.
SOFTWARE ENGINEER, VOICE MODEL
You'll join the Grok Voice Model team as a software engineer. You'll design, build, and run the software systems behind Grok Voice, which 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 to distributed training to production deployment.
RESPONSIBILITIES:
Design, build, and maintain large-scale distributed data pipelines that ingest, process, and annotate real-world and synthetic audio, so the training and evaluation systems get reliable, high-quality data
Build and optimize the distributed training infrastructure and software for speech-language models in JAX and PyTorch, including the systems that run supervised fine-tuning and reinforcement learning at scale
Build automated evaluation and testing systems that measure accuracy, audio quality, latency, and real-time performance, plus the experimentation infrastructure used to validate every model release
Integrate voice models into production applications and real-time services, write the technical specifications for spoken interactions, and own deployment from prototype to global scale with a focus on stability, low latency, and reliability
Profile and optimize system performance across training and inference, including throughput, latency, memory use, and compute efficiency
BASIC QUALIFICATIONS:
Bachelor's degree in computer science, software engineering, computer engineering, electrical engineering, or another engineering discipline
Experience building and running large-scale distributed training and inference systems on Kubernetes
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
PREFERRED SKILLS AND EXPERIENCE:
Expert-level Python, writing clean, efficient, production-quality code for large-scale systems
Hands-on experience building distributed data processing systems with tools like Spark and Ray
A proactive, self-driven attitude and the ability to deliver in a fast-paced, high-caliber team
COMPENSATION AND BENEFITS:
$150,000 - $450,000 USD
Base salary is just one part of our total rewards package at SpaceXSI, which also includes equity, comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short & long-term disability insurance, life insurance, and various other discounts and perks.
SpaceXSI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.
Pay, skills & work eligibility
Compensation
A clear compensation amount was not identified. Ask the employer for the range, currency, pay period and whether it covers base pay or total compensation.
Location, eligibility & working hours
- Listed work location
- Palo Alto, CA
- Visa sponsorship
- Not stated clearly
- Relocation support
- Not stated clearly
- Working hours / time zone
- Not stated clearly
Remote does not automatically mean work from any country. A location match does not confirm work authorization, sponsorship or relocation eligibility.
Requirements at a glance
Named skills identified in the listing. A mention is not always a requirement; read the full description and employer conditions.