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# software engineer

- **Company:** Space X
- **Location:** United States
- **Experience:** Experienced
- **Salary:** $220,000
- **Contract:** Permanent contract
- **Skills:** Automation of Tests, C++ (Programming Language), Computer Engineering, Distributed Computing Environment, Distributed Data Store, Python (Programming Language), Language Modeling, Performance Tuning, Software Engineering, Reinforcement Learning, Pytorch, Apache Spark, Kubernetes, Information Technology, Low Latency, Production Code
- **Published:** November 7, 2026
- **Apply:** https://startup.jobs/sr-model-engineer-voice-xai-10714490

## About the Role

* 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++
 * 2+ years of experience working with large scale voice related products, * Experience building and running large-scale distributed training and inference systems on Kubernetes
 * Expert-level Python, 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 like Spark and Ray
 * A proactive, self-driven attitude and the ability to deliver in a fast-paced, high-caliber team

## Description

* 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