Senior Principal Machine Learning Engineer

About the team

The ML team builds and optimizes the models that run on SambaNova's RDU accelerators. Their work covers model architecture, training and fine-tuning, inference optimization, evaluation, and data curation, and it lands in SambaStack and SambaCloud. They work directly with the compiler, systems, and hardware teams on co-design, so decisions about a model shape decisions about the silicon it runs on.

About the role

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.

Responsibilities

Some of your responsibilities will include:

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

Required Qualifications

B.S. in Computer Science, Electrical Engineering, or related field

8+ years of industry experience in machine learning engineering, with a demonstrated record of technical leadership on large-scale or novel ML systems

Deep expertise in LLM training, fine-tuning, inference optimization, and evaluation at scale

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

Track record of independently scoping and delivering high-complexity, high-ambiguity technical projects

Preferred Qualifications

M.S. or Ph.D. in Computer Science, Electrical Engineering, or related field

Experience with hardware-software co-design with non-GPU accelerators

Publications or open-source contributions in LLM training or inference

Experience with speculative decoding, mixture-of-experts, or long-context modeling in production

Experience with reinforcement learning for post-training

Familiarity with compiler or kernel-level optimization for ML workloads

Base Salary Range:

Base Pay Range

$220,000—$300,000 USD