Technical Staff for Model Training

Taking technical ownership of distributed systems and platforms, the full-time remote Member of Technical Staff for Model Training will architect and optimize infrastructure for machine learning, enabling researchers to execute large-scale experiments and deploy AI systems efficiently. Key responsibilities Architect, build, and scale shared infrastructure for supervised fine-tuning, reinforcement learning, and on-policy distillation Design distributed training and execution pipelines that coordinate GPU workers and optimize model inference Lead critical engineering initiatives, mentoring engineers while maintaining ownership of complex components Required qualifications Strong fundamentals in computer science, particularly in distributed systems and performance engineering Extensive experience in designing and operating scalable backend systems or distributed computing platforms Proficiency in Python and at least one systems-oriented programming language (C++, Rust, or Go) Hands-on experience with GPU-based machine learning infrastructure and distributed training Demonstrated technical ownership and ability to lead cross-functional initiatives in fast-paced environments