Builds state-of-the-art document processing infrastructure using LLMs, including QA agents, optimizers, multimodal models, and self-correcting systems. Monitors production models, runs experiments, and owns large product areas for real-world customer impact.
Develop and optimize GPU kernels and deep learning systems for LLM training and inference at Snowflake AI Research. Requires 5+ years in GPU/HPC optimization and strong proficiency in PyTorch, TensorFlow, JAX, and CUDA.
Build in-house tooling for post-training custom ML models using advanced techniques like RL and finetuning. Requires deep expertise in transformer training, PyTorch distributed systems, parallelism strategies, GPU performance optimization, and HPC platforms.
Develop ML systems for the Enterprise Brain, focusing on proactive AI for task prediction, automation, and agentic workflows using LLMs and advanced techniques. Requires 3+ years ML experience, Python proficiency, and expertise in evaluation and production systems.
Designs, fine-tunes, and deploys image generation models for photorealistic AI bots, optimizing for consistency, latency, and quality. Requires 5+ years software engineering, 2+ years production ML, and expertise in diffusion models like Stable Diffusion and PyTorch.
Research Engineer building production ML systems at the intersection of efficient inference, RL/post-training, and serving engines. Translates algorithms into scalable infrastructure improving latency, throughput, and model quality. Requires 3+ years ML systems experience and advanced degree.