Senior Machine Learning Engineer, AWS Generative AI Innovation Center

Amazon

Amazon

Software Engineering, Data Science

Tokyo, Japan

Posted on Jun 2, 2026

Description

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI.

The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof-of-concepts, and make plans for launching solutions at scale. The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently.

You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.

We’re looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the-art solutions for never-before-solved problems.

Key job responsibilities
Our ML Engineers collaborate across diverse teams, projects, and environments to have a firsthand impact on our global customer base. You’ll bring a passion for the intersection of software development with generative AI and machine learning. You’ll also:

- Solve complex technical problems, often ones not solved before, at every layer of the stack.
- Design, implement, test, deploy and maintain innovative GenAI solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
- Complexities will include distributed model training; low latency and high throughput model hosting.
- Will work along with scientists on SLM/LLM optimization/finetuning



A day in the life
As you design and code solutions to help our team drive efficiencies in ML architecture, you’ll create metrics, implement automation and other improvements, and resolve the root cause of software defects. You’ll also:

- Build high-impact ML solutions to deliver to our large customer base.
- Participate in design discussions, code review, and communicate with internal and external stakeholders.
- Work cross-functionally to help drive business solutions with your technical input.
- Work in a startup-like development environment, where you’re always working on the most important stuff.



About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.