Senior Principal Machine Learning Engineer

• 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
• Define and drive technical strategy for ML model development, training pipelines, and inference systems on SambaNova’s RDU and broader hardware ecosystem
• Lead hardware-software co-design efforts in close collaboration with compiler, systems, and hardware teams—shaping architectural decisions that unlock performance at scale
• Identify, evaluate, and champion state-of-the-art ML techniques (e.g., speculative decoding, reinforcement learning, mixture-of-experts, long-context modeling) for adoption and adaptation on reconfigurable dataflow architectures
• Serve as the senior technical voice in critical design reviews, architectural decisions, and cross-functional planning—providing guidance that influences product and engineering roadmaps
• Mentor and develop principal and senior ML engineers, elevating the technical capabilities of the organization through active collaboration, design feedback, and knowledge transfer
• Partner with product and engineering leadership to translate complex ML capabilities into scalable, customer-facing solutions in SambaStack and SambaCloud
• Drive resolution of the most complex, ambiguous technical challenges—including those that span organizational boundaries or require novel approaches not yet established in the field

Benefits

• Flexible PTO in US
• Parental Leave
• Benefits (medical, dental and vision)
• Flexible Spending Accounts
• 401k/Pensions
• Gym Access
• Flexible Working Hours- Track record of independently scoping and delivering high-complexity, high-ambiguity technical projects
• Bachelor’s degree in Computer Science, Electrical Engineering, or related field; advanced degree (MS or PhD) strongly preferred
• Deep expertise in LLM training, fine-tuning, inference optimization, and evaluation at scale
• 8+ years of industry experience in machine learning engineering, with a demonstrated record of technical leadership on large-scale or novel ML systems
• Strong background in ML algorithms, deep learning architectures, and modern training methodologies, with the ability to critically evaluate and advance the state of the art
• Demonstrated ability to lead and align cross-functional technical efforts, mentor senior engineers, and influence organizational direction without direct management authority