Member of Technical Staff (Reinforcement Learning Infrastructure), AGI Autonomy

Amazon; San Francisco (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

An innovative company is seeking a Member of Technical Staff to join their AGI Autonomy team in San Francisco. This role focuses on developing cutting-edge reinforcement learning systems that empower AI agents to operate effectively in diverse environments. You will collaborate with researchers to design and maintain robust training infrastructure, ensuring efficiency in large-scale machine learning processes. This position offers a unique blend of startup agility and the extensive resources of a major tech player, providing an exciting opportunity to contribute to groundbreaking AI research and applications. If you are passionate about advancing AI technology and enjoy tackling complex challenges, this role is perfect for you.

Qualifications

• PhD or Master's degree with 3+ years of applied research experience.
• Experience programming in Java, C++, Python or related languages.

Responsibilities

• Develop training infrastructure for large-scale reinforcement learning.
• Analyze and troubleshoot complex ML systems to improve performance.

Skills

Java

C++

Python

Machine Learning

Neural Deep Learning Methods

Debugging ML Systems

Education

PhD in Computer Science or related field

Master's degree with 3+ years of experience

Tools

Megatron

vLLM

Ray

GPUs

Job description

Member of Technical Staff - Reinforcement Learning (Infrastructure), AGI Autonomy

Job ID: 2902948 | Amazon.com Services LLC

The Amazon AGI SF Lab is focused on developing new foundational capabilities for enabling useful AI agents that can take actions in the digital and physical worlds. We’re enabling practical AI that can actually do things for us and make our customers more productive, empowered, and fulfilled.

The lab is designed to empower AI researchers and engineers to make major breakthroughs with speed and focus toward this goal. Our philosophy combines the agility of a startup with the resources of Amazon. By keeping the team lean, we’re able to maximize the amount of compute per person. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research.

In this role, you will work closely with research teams to design, build, and maintain systems for training and evaluating state-of-the-art agent models.

Key job responsibilities:

1. Develop cutting-edge training infrastructure to ensure large-scale reinforcement learning on LLMs runs highly efficient and robust.
2. Work across the entire technology stack, including low level ML system, job orchestration and data management.
3. Analyze, troubleshoot and profile complex ML systems, identify and address performance bottlenecks.
4. Work closely with researchers, conduct MLSys research to create new techniques, infrastructure, and tooling around emerging research capabilities.

BASIC QUALIFICATIONS

- PhD, or Master's degree and 3+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Experience debugging ML systems

PREFERRED QUALIFICATIONS

- PhD in Computer Science, Machine Learning, or a related field, with a focus on ML System.
- Demonstrated experience in developing, implementing and debugging large scale ML systems.
- Experience with distributed systems, Megatron, vLLM, Ray, and working with GPUs.
- Experience with patents or publications at top-tier peer-reviewed conferences or journals.