资深机器学习工程师，AI工作室

Join the AI Studios Engineering org within Prime Video and Amazon MGM Studios as a Machine Learning Engineer on CreativeFlux, the ML platform powering Nara, our AI-native content creation platform for professional animation and live action/VFX.

You will own the training and serving infrastructure that puts generative models in front of artists working on Prime Video's animated and live action productions.

You'll work daily with Applied Scientists, animators, filmmakers, and storytellers, building the systems that turn new model architectures into production-grade tools artists can rely on under tight deadlines.

This role suits engineers who want their work to expand what storytelling can look like, putting new generative capabilities into the hands of the people building Prime Video's animated and live action shows.

Design, deploy, and operate ML training and inference workloads on EKS, including GPU node groups, custom schedulers, autoscaling, resource quotas, and gang scheduling for multi-GPU jobs

Integrate generative ML models (image, video, audio) into production inference pipelines, partnering with Applied Scientists to take new architectures from research to scaled deployment Build training and fine-tuning pipelines on EKS and SageMaker, including data preparation, distributed training, evaluation harnesses, and checkpointing strategies Improve GPU utilization, throughput, and latency on the inference fleet through batching, quantization, model compilation, serving framework tuning, and Kubernetes-native scaling primitives (HPA, KEDA, custom controllers) Build automated evaluation pipelines and quality metrics that catch model regressions before they reach Artists, including human-in-the-loop review where needed Drive integrations with Digital Content Creation (DCC) tools such as Adobe Animate, After Effects, Maya, and Storyboard Pro at the points where models are surfaced to creators Own operational health of model endpoints on EKS, including monitoring, alerting, on-call response, capacity planning, and post-incident analysis

Write clean, well-tested code and participate in design and code reviews Stay current with generative ML, distributed training, inference optimization, and GPU efficiency techniques, and apply them to move team metrics A day in the life

As an MLE on the AI Studios team, you'll deploy and tune generative ML models, optimizing inference pipelines, and build EKS infrastructure that empowers Scientists productionalize new model architectures.

A typical day includes scaling video generation endpoints, debugging multi-GPU training pipelines, or supporting a Scientist to migrate a new image model from a research notebook to a serving fleet.

You'll work with other Nara platform teams to ensure ML capabilities land cleanly in production artists workflows.

You'll join team standups, model review sessions, on-call rotations, and platform-wide design reviews.

You'll learn from experienced engineers and scientists to gradually take on more complex challenges over time.

We're AI Studios within Prime Video and Amazon MGM Studios, building Nara, our AI-native content creation platform.

Our mission is to make Amazon a leader in AI-enabled content creation, giving creators direct control over model outputs while reducing the cost and timeline of animation and live action productions.

Our engineering team spans distributed systems engineers building scalable infrastructure, ML engineers optimizing 1P model training and inference, and full-stack engineers building creative facing agentic tools.

- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience

- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service;

and follow all federal, state, and local laws and Company policies.

Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position.

These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation.

Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers.

If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information.

If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

The base salary range for this position is listed below.

Your Amazon package will include sign-on payments and restricted stock units (RSUs).

Final compensation will be determined based on factors including experience, qualifications, and location.

Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave.