SDE II, ML Infra Services, Annapurna Labs

Description

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. AWS is an infrastructure company, and Annapurna Labs provides the infrastructure for AWS, covering areas such as silicon engineering, hardware design and verification, software, and operations. Some of the products delivered by Annapurna Labs include AWS Nitro, ENA, EFA, Graviton, and F1 EC2 Instances, AWS Neuron, Inferentia, and Trainium ML Accelerators, and scalable NVMe storage.

Key job responsibilities

• Lead the development of machine learning tools to run, optimize, and analyze machine learning workloads.
• Design and implement ML infrastructure platform, building systems for capacity management, workload scheduling, and fleet orchestration across ML accelerators.
• Work with ML scientists, training infrastructure engineers, hardware teams, and internal customers to ensure the ML Infra service delivers seamless ML Accelerator access with low wait times, high utilization, and zero-config deployment from various environments.

About The Team

This position is for a Software Engineer that will lead the development of machine learning tools to run, optimize, and analyze machine learning workloads. This candidate must have had experience leading machine learning tool projects, preferably starting from architecture through several generations of delivery to customers. Deep knowledge of profiling and optimization, resource management, scheduling, code generation are needed. The ideal candidate will have worked on new instruction set architectures, which may include CPU, NPU, GPU and other forms of compute.

Basic Qualifications

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience programming with at least one software programming language

PREFERRED QUALIFICATIONS

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor's degree in computer science or equivalent
• Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
• Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS
• Experience in Kubernetes, Docker or containers ecosystem, or experience managing full application stacks from the OS up through custom applications and experience in any Bigdata architecture
• Strong proficiency in Go/Java, Python, and Javascript/Typescript
• Application and kernel performance profiling and optimization
• Proficiency in integrated software/hardware performance analysis and optimization
• Experience designing and operating production services