AI/ML Software Engineer II: High-Performance Inference

Amazon; Cupertino (CA); On-site; USD 165,000 - 224,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. in Cupertino, CA is seeking a Software Engineer II - AI/ML to design, optimize and deploy ML workloads on AWS Trainium accelerators.

You will work across Python, C++, and low-level kernels, collaborating with compiler, runtime, and hardware teams to maximize model performance and efficiency at scale. You will participate in all stages of the ML system lifecycle, from prototyping to production, and work closely with customers to enable and optimize their models on AWS

Qualifications

• 3+ years of non-internship professional software development experience.
• Bachelor's degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field.
• Knowledge of Python and/or C++ programming.
• 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
• 1+ years of designing and developing large-scale, multi-tiered software applications using C++, Java, or similar languages.

Responsibilities

• Design, develop, and optimize ML models and frameworks for deployment on custom ML hardware accelerators.
• Participate in all stages of the ML system development lifecycle, including distributed computing architecture design and production deployment.
• Build infrastructure to analyze and onboard multiple models with diverse architectures.
• Understand and implement high-performance kernels and features for ML operations leveraging the Neuron architecture.

Skills

Python

C++

Distributed systems

Performance optimization

Debugging

Education

Bachelor's degree in CS/Engineering/Math

Tools

CUDA

Triton

PyTorch

JIT

Job description

Annapurna Labs (U.S.) Inc. in Cupertino, CA is seeking a Software Engineer II - AI/ML to design, optimize and deploy ML workloads on AWS Trainium accelerators.

You will work across Python, C++, and low-level kernels, collaborating with compiler, runtime, and hardware teams to maximize model performance and efficiency at scale. You will participate in all stages of the ML system lifecycle, from prototyping to production, and work closely with customers to enable and optimize their models on AWS