Applied Machine Learning Research Scientist
Core
Turning modern machine learning techniques into scalable, high-performance systems for large language models (LLMs) and reinforcement learning, focusing on production implementation rather than publishing new algorithms.
Role type
Applied Machine Learning Research Scientist (hands-on IC)
Builds
Scalable training pipelines, evaluation frameworks, and optimized inference workflows for LLMs
Domain
Artificial Intelligence / Large Language Models / Reinforcement Learning
Deliverable
production ML models
Required skills
Python, PyTorch, machine learning fundamentals, deep learning architectures (transformers), reading and implementing ML papers
Preferred skills
Large language model training and fine-tuning, reinforcement learning concepts, distributed training frameworks (FSDP, Megatron), large-scale data pipelines, system optimization
Technologies
Python, PyTorch, FSDP, Megatron
Responsibilities
Apply post-training techniques (RLVR, RLHF, GRPO) to improve model performance; Build and maintain evaluation pipelines; Debug issues across the ML stack (data pipelines, training jobs, mixed precision); Collaborate to translate ML ideas into efficient implementations; Design and scale ML pipelines across LLM development stages; Work with large datasets including generation and filtering; Optimize training and inference workflows; Contribute maintainable code to shared ML infrastructure
Seniority
Mid-level (4+ years experience)