Machine Learning Engineer - New Grad

The Machine Learning team builds the model-side techniques that make SambaNova’s platform fast and capable. We train speculative decoding models that accelerate inference, develop efficient ML methods such as quantization, sparsity, and distillation, and build agentic systems on top of our foundation model serving stack. Our work spans research, applied science, and production, from novel approach design to proofs of concept and shipping to product. Reinforcement learning and post-training are within our scope and a growing part of our roadmap.

As a new grad Machine Learning Engineer, you’ll train and evaluate models that make large language models cheaper and more capable to serve. Depending on your interests, that could mean training speculator (draft) models and tuning acceptance rates, compressing models without losing accuracy, or designing and evaluating agentic workflows for tool use, planning, and long-horizon tasks. You’ll work closely with the AI performance, compiler, and runtime teams to turn research results into measured end-to-end wins, and you’ll have room to pursue open problems as our reinforcement learning and post-training work ramps up.

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