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Senior Principal Machine Learning Engineer

SambaNova Systems · San Jose, CA · Posted 81 days ago

$220k–$300kmgr
Large Language Models (LLM)Machine LearningDeep LearningModel TrainingFine-tuningInference OptimizationHardware-Software Co-designML Algorithms

The era of pervasive AI has arrived. In this era, organizations will use generative AI to unlock hidden value in their data, accelerate processes, reduce costs, drive efficiency and innovation to fundamentally transform their businesses and operations at scale.

SambaNova Suite™ is the first full-stack, generative AI platform, from chip to model, optimized for enterprise and government organizations. Powered by the intelligent SN40L chip, the SambaNova Suite is a fully integrated platform, delivered on-premises or in the cloud, combined with state-of-the-art open-source models that can be easily and securely fine-tuned using customer data for greater accuracy. Once adapted with customer data, customers retain model ownership in perpetuity, so they can turn generative AI into one of their most valuable assets.

Overview

As a Senior Principal Machine Learning Engineer, you will be responsible for designing, developing, and optimizing machine learning models—with a focus on cutting-edge Large Language Models (LLMs)—to run efficiently on SambaNova's specialized hardware architecture, including the RDU. This critical role bridges advanced LLM research and practical deployment, involving the development of model architectures, improving training and inference efficiency, and collaborating on hardware-software co-design with compiler, systems, and hardware teams. The engineer will also act as the ML expert, guiding the integration of LLM solutions into production systems and customer-facing products like SambaStack and SambaCloud, with work spanning the full lifecycle from training and inference to evaluation and data curation.

Qualifications

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Related roles

There are 73 open roles at SambaNova Systems right now. This role is one of 24 Machine Learning Engineer openings in San Jose, CA and centers on Large Language Models (llm), Machine Learning, Deep Learning, and Llm Training.

See this month's Hiring Index: Fabs Are Closing. Design Isn't. for the broader trend behind roles like this one.

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