Compiler Architect

SambaNova is a leader in next-generation AI infrastructure, delivering a full-stack inference platform for customers worldwide. At the core of SambaNova's technology is the RDU (Reconfigurable Dataflow Unit) — a chip built on a dataflow architecture rather than the traditional GPU model. Its decode performance is especially strong for agentic workloads like multi-turn agents, code generation, and long-running applications. RDUs are packaged into SambaRack, rack-scale hardware that lets customers deploy state-of-the-art models with better performance, greater energy efficiency, and faster time to value.

About the Role

As a Compiler Architect you will be responsible for working with the different layers of the compiler stack and coordinating with other development teams here at SambaNova. It is a critical role responsible for driving innovation in compiler infrastructure and optimization algorithms that enable state-of-the-art ML model performance on the SambaNova platform. This can involve anything from digging through PyTorch and machine learning models to determining how to map operations on to our underlying hardware.

Responsibilities

• Lead compiler engineering through ensuring standard methodologies, enterprise product insertion and process evolution.
• Work with peers, domain experts, developers, customers, and work across the enterprise seeking optimal solutions.
• Develop, integrate, and implement products.
• Provide support for proposals in key areas aligned with core team competencies.

Basic Qualifications

• Bachelor’s or Master’s Degree in Computer Science, Computer Engineering, or equivalent with 5-10 years of industry experience.

Additional Qualifications

• Deep theoretical understanding of compiler fundamentals.
• Experience building and deploying software products.
• Experience with one or more deep learning frameworks (i.e. TensorFlow, PyTorch) is a plus.
• Experience with common compiler development practices and methodologies.
• Excitement about high-performance systems engineering and performance debugging.
• An appreciation for process and developing cross-disciplinary collaboration.

Preferred Qualifications

• Experience with MLIR.
• Familiarity with machine learning models and frameworks.
• Familiarity with accelerated computing.
• Exposure to dataflow architectures.

Base Salary Range: