Роль хорошо очерчена и связана с заметным продуктом в сфере голосового ИИ: зона ответственности охватывает данные, обучение, оценку и запуск моделей. При этом заявленная культура быстрых темпов может означать высокую нагрузку.
Высокий темп
Передовые технологии
Голосовой ИИ
Полный цикл
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Sr. Model Engineer (Voice) (JAX/PyTorch): Building distributed data, training, evaluation, and production systems for Grok Voice with an accent on multilingual, low-latency spoken interactions and large-scale model infrastructure. Focus on optimizing speech-language model training and inference, deploying real-time voice services, and ensuring reliability, audio quality, and compute efficiency.
Location: Palo Alto, California, United States
Salary: $220,000–$357,000 USD per year
Company
xAI is building Super Intelligence across compute infrastructure, Grok models, and applications including Grok Voice.
What you will do
Design, build, and maintain distributed data pipelines for real-world and synthetic audio ingestion, processing, and annotation.
Develop and optimize distributed training infrastructure for speech-language models in JAX and PyTorch, including supervised fine-tuning and reinforcement learning.
Build automated evaluation, testing, experimentation, and A/B systems measuring accuracy, audio quality, latency, and real-time performance.
Integrate voice models into production applications and real-time services, defining spoken-interaction specifications and owning deployment from prototype to global scale.
Profile and optimize training and inference performance across throughput, latency, memory usage, and compute efficiency.
Requirements
Bachelor’s degree in computer science, software engineering, computer engineering, electrical engineering, or another engineering discipline.
Production-quality coding experience in Python, PyTorch, JAX, Rust, or C++.
2+ years of experience working with large-scale voice-related products.
Nice to have
Experience building and operating large-scale distributed training and inference systems on Kubernetes.
Expert-level Python skills and experience 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 with distributed data processing systems such as Spark and Ray.
Proactive, self-driven approach and ability to deliver in a fast-paced, high-caliber team.
Culture & Benefits
Work on natural, low-latency, multilingual voice interactions across devices in real time.
Comprehensive medical, vision, and dental coverage.
Equity, 401(k) retirement plan, short- and long-term disability insurance, and life insurance.
Additional discounts and perks.
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