Compiler Engineer (Backend)

DESCRIPTION

As Compiler Backend Engineer, you will be a key player in expanding the Backend functionality and optimizations for the Celestial AI Machine Learning accelerator architecture. We have opportunities in the areas of code generation, partitioning, kernel generation, and runtime interfaces. This role is highly collaborative with Architecture, Hardware, and ML Operations and Developers to ensure Compiler requirements and tools to achieve exceptional performance are met. The Hardware and Instruction Set Architecture (ISA) are driven from a Compiler perspective with the goal of rapidly delivering full functionality and performance across a broad spectrum of ML models with minimal Compiler complexity. The compiler design flow is iterative and fast-paced.

ESSENTIAL DUTIES AND RESPONSIBILITIES

• Design, prototype, and expand the functionality and performance of the compiler in the areas of code generation, partitioning, kernel generation, and/or runtime interfaces
• Benchmark, test, and analyze output produced by the compiler
• Work with HW teams and architects to drive improvements in architecture and SW compiler

QUALIFICATIONS

• BS or MS in Computer Science, Engineering, or related field
• 2+ years of experience in compilers for data parallel architectures
• Experience in the field of compilers for Machine Learning inference models, preferred
• Experience with the Apache TVM Hardware Backend codebase and workflow for custom code generators (BYOC), preferred
• Effective communicator and collaborator

For California location:

As an early startup experiencing explosive growth, we offer an extremely attractive total compensation package, inclusive of competitive base salary and a generous grant of our valuable early-stage equity. The target base salary for this role is approximately $155,000.00 - $175,000.00. The base salary offered may be slightly higher or lower than the target base salary, based on the final scope as determined by the depth of the experience and skills demonstrated by candidate in the interviews.

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