ML Compiler Engineer, Annapurna Labs

Cupertino, CA

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About the position

The AWS Neuron Compiler team is actively seeking skilled compiler engineers to join our efforts in developing a state-of-the-art deep learning compiler stack. This stack is designed to optimize application models across diverse domains, including Large Language and Vision, originating from leading frameworks such as PyTorch, TensorFlow, and JAX. Your role will involve working closely with our custom-built Machine Learning accelerators, including Inferentia/Trainium, which represent the forefront of AWS innovation for advanced ML capabilities, powering solutions like Generative AI. In this role as a ML Compiler engineer, you'll be instrumental in designing, developing, and optimizing features for our compiler. Your responsibilities will involve tackling crucial challenges alongside a talented engineering team, contributing to leading-edge design and research in compiler technology and deep-learning systems software. Additionally, you'll collaborate closely with cross-functional team members from the Runtime, Frameworks, and Hardware teams to ensure system-wide performance optimization. As part of the Backend team, you'll play a significant role in designing and developing various aspects of our system. This includes but is not limited to instruction scheduling, memory allocation, data transfer optimization, graph partitioning, parallel programing, code generation, Instruction Set Architectures, new hardware bring-up, and hardware-software co-design. AWS Utility Computing (UC) provides product innovations that continue to set AWS's services and features apart in the industry. As a member of the UC organization, you'll support the development and management of Compute, Database, Storage, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon's growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.

Responsibilities

• Solve challenging technical problems, often ones not solved before, at every layer of the stack.
• Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
• Research implementations that deliver the best possible experiences for customers.
• Build high-impact solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business decisions with your technical input.
• Work in a startup-like development environment, where you're always working on the most important stuff.

Requirements

• B.S. or M.S. in computer science or related field
• Proficiency with 1 or more of the following programming languages: C++ (preferred), Python
• 3+ years of non-internship professional software development experience
• 2+ years of experience developing compiler optimization, graph-theory, hardware bring-up, FPGA placement and routing algorithms, or hardware resource management

Nice-to-haves

• M.S. or Ph.D. in computer science or related field
• Strong knowledge in one or more of the areas of: compiler design, instruction scheduling, memory allocation, data transfer optimization, graph partitioning, parallel programing, code generation, Instruction Set Architectures, new hardware bring-up, and hardware-software co-design
• Experience with LLVM and/or MLIR
• Experience with developing algorithms for simulation tools
• Experience is TensorFlow, PyTorch, and/or JAX
• Experience in LLM, Vision or other deep-learning models