GenAI ML Engineer: Frontier Assets & Tools

Amazon; Boston (MA); On-site; USD 144,000 - 194,000; Full time

Job summary

Amazon Inc. is seeking an MLE to design, build, and maintain systems for frontier quality assets used to train and evaluate GenAI models.

You will collaborate with Applied Scientists to develop tools supporting modeling and evaluation, working at scale with cutting-edge research. The role emphasizes building agentic pipelines, partnering with product teams, and delivering high-quality software under tight schedules, in a dynamic environment with an inclusive culture.

Qualifications

• 3+ years of non-internship professional software development experience.
• 3+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems.
• 3+ years of designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using C#, C++, Java, or Perl.
• 1+ years of Object Oriented Design experience.
• Experience programming with at least one software programming language.

Responsibilities

• Develop and maintain key tooling for building agentic pipelines to create frontier-level assets, such as RL gyms.
• Work closely with product teams and scientists to create new techniques and tooling around emerging research capabilities and evaluating models to meet customer needs.
• Collaborate closely with Applied Scientists to investigate and plan experiments, prototype new technology, and evaluate technical feasibility.
• Operate in a dynamic environment to deliver high-quality software against tight schedules.

Skills

C++

Java

C#

Perl

Object Oriented Design

Distributed systems

Education

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field

Job description

Amazon Inc. is seeking an MLE to design, build, and maintain systems for frontier quality assets used to train and evaluate GenAI models.

You will collaborate with Applied Scientists to develop tools supporting modeling and evaluation, working at scale with cutting-edge research. The role emphasizes building agentic pipelines, partnering with product teams, and delivering high-quality software under tight schedules, in a dynamic environment with an inclusive culture.