Principal SDE, ML | Reinforcement Learning, AGI Foundations
Amazon
Description
The Artificial General Intelligence (AGI) Foundations team is looking for a passionate, talented, and inventive Principal ML Engineer with strong machine learning background, to lead the development of industry-leading technology.
As a Principal Software Engineer, ML within the Artificial General Intelligence (AGI) organization, you are a trusted part of the technical leadership. You bring business and industry context to technology decisions.
You will be responsible for leading the development of novel algorithms and techniques to advance the state of Large Language Model (LLM) training. You will leverage Amazon’s heterogeneous data sources and large-scale computing resources to accelerate development of multimodal Large Language Models and Generative Artificial Intelligence solutions. You will collaborate closely with the Applied Scientists on LLM reinforcement learning techniques to build production training workflows.
You set the standard for engineering excellence and make decisions that affect the way we build and integrate algorithms. Your solutions are exemplary in terms of system design, clarity, efficiency, and extensibility. You tackle intrinsically hard problems; you're interested in learning; and you acquire skills and expertise as needed. Your expertise is deep and broad; you’re hands on, producing both detailed technical work and high-level architectural designs.
You help managers guide the career growth of other engineers by mentoring and play a significant role in hiring and developing engineers and leads.
You will play a critical role in driving the development of Generative AI (GenAI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences.
Key job responsibilities
Serve as a technical lead on our most demanding, cross-functional projects.
Ensure the quality of architecture and design of systems.
Functionally decompose complex problems into simple, straight-forward solutions.
Fully and completely understand system interdependencies and limitations.
Possess expert knowledge in performance, scalability, enterprise system architecture, and engineering best practices.
Leverage knowledge of internal and industry prior art in design decisions.
Effectively research and benchmark Amazon technology against other competing systems in the industry.
Contribute intellectual property through patents.
Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members.
Exert technical influence over multiple teams, increasing their productivity and effectiveness by sharing your deep knowledge and experience.