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

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

Job summary

An innovative research lab in San Francisco is seeking a talented individual to join their team focused on developing advanced AI capabilities. The role involves designing scalable simulation environments and utilizing generative AI to enhance training processes for AI agents. This is a unique opportunity to work at the forefront of AI research, where you'll collaborate with experts from various fields to tackle challenging problems. If you're passionate about machine learning and eager to contribute to groundbreaking projects, this position offers an exciting path to make a significant impact in the AI landscape.

Qualifications

• PhD or Master's degree with 5+ years of applied research experience required.
• Strong programming skills in C++ and Python, with experience in machine learning.

Responsibilities

• Design and implement scalable simulation environments for training AI agents.
• Collaborate with teams to solve complex problems in AI and reinforcement learning.

Skills

C++

Python

Machine Learning

Problem Solving

Collaboration

Education

PhD in Computer Science

Master's degree

5+ years of applied research experience

Tools

TensorFlow

PyTorch

Job description

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

Job ID: 2937537 | Amazon.com Services LLC

Amazon has launched a new research lab in San Francisco to develop foundational capabilities for useful AI agents. We’re enabling practical AI to make our customers more productive, empowered, and fulfilled. In particular, our work combines large language models (LLMs) with reinforcement learning (RL) to solve reasoning, planning, and world modeling in both virtual and physical environments. Our research builds on that of Amazon’s broader AGI organization, which recently introduced Amazon Nova, a new generation of state-of-the-art foundation models (FMs).

Our lab is a small, talent-dense team with the resources and scale of Amazon. Each team in the lab has the autonomy to move fast and the long-term commitment to pursue high-risk, high-payoff research. We’re entering an exciting new era where agents can redefine what AI makes possible. We’d love for you to join our lab and build it from the ground up!

Key job responsibilities

1. Design and implement highly scalable and realistic simulation environments for training agents using reinforcement learning.
2. Develop and deploy generative AI approaches to automate the creation of diverse and complex simulation environments and scenarios.
3. Analyze, troubleshoot, and profile complex machine learning systems within the simulation context, identifying and resolving performance bottlenecks.
4. Collaborate with cross-functional teams – including engineers, product managers, and scientists – to identify and solve challenging problems at the intersection of generative AI and reinforcement learning.

BASIC QUALIFICATIONS

1. PhD, or Master's degree or 5+ years of applied research experience
2. Experience programming in C++, Python or related language
3. Experience with simulation and synthetic data generation
4. Experience with neural deep learning methods and machine learning

PREFERRED QUALIFICATIONS

1. PhD in Computer Science, Machine Learning, or a related field
2. 3+ years' experience building machine learning models (includes internships)
3. Demonstrated experience in developing and implementing simulation environments or synthetic data generation for reinforcement learning.
4. Strong programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch
5. Excellent problem-solving skills, with the ability to think creatively and critically about complex problems
6. Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.