---
title: Senior MLE, CreativeFlux, AI Studios at Amazon
description: Amazon is hiring for the Senior MLE, CreativeFlux, AI Studios role in Culver City,
  CA. Full-time role. See the full description and apply.
type: job
url: https://www.foundrole.com/jobs/senior-mle-creativeflux-ai-studios-at-amazon-01a136a8-497d-74fa-b0e4-656eb0ef4f34
date: 2026-11-15T01:26:44Z
og_description: Join Amazon as Senior MLE, CreativeFlux, AI Studios in Culver City, CA. Pays $168.1K–$227.4K
  per year. Full-time role.
og_image: https://www.foundrole.com/og/mzupa5.png
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---

| | |
|---|---|
| **Company** | [Amazon](https://www.foundrole.com/companies/amazon?utm_source=ai_markdown) |
| **Location** | Culver City, CA |
| **Salary** | $168.1K/yr - $227.4K/yr |
| **Type** | Intern |
| **Posted** | Oct 13, 2026 |

## Is this job real?

**Ghost job check:** A- · Low risk. Probably a real opening.

## Visa sponsorship

- **H-1B:** Amazon sponsors H-1B visas. It filed 25,968 H-1B petitions (FY2026 Q1 – FY2026 Q4).
- **E-Verify:** No E-Verify enrollment on record for Amazon.

## Pay for similar jobs

Most similar jobs pay $178,000 – $227,000 a year (median $208,000).

## Description

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.  

Key job responsibilities  
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.  

About the team  
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.

## Basic Qualifications

\- 5+ years of non-internship professional software development experience  
\- 5+ years of programming with at least one software programming language experience  
\- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience  
\- Experience as a mentor, tech lead or leading an engineering team

## Preferred Qualifications

\- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience  
\- Bachelor's degree in computer science or equivalent  

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; 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 <https://amazon.jobs/content/en/how-we-hire/accommodations> 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. Learn more about our benefits at <https://amazon.jobs/en/benefits>.

USA, CA, Culver City - 168,100.00 - 227,400.00 USD annually  
USA, NY, New York - 184,900.00 - 250,200.00 USD annually
## Skills

- AWS SageMaker
- Technical Leadership
- GPU Computing
- Autoscaling
- Coding Standards
- Storyboarding
- Software Deployment
- Code Review
- Machine Learning Model Fine-Tuning
- Software Design Patterns
- Adobe After Effects
- Data Preparation
- Software Development
- Software Development Life Cycle
- Evaluation Pipelines
- Distributed Training (Machine Learning)
- Machine Learning Inference
- Quality Metrics and KPIs
- GPU (Graphics Processing Unit)
- Computer Science
- Version Control
- Digital Content Creation
- Human-in-the-Loop
- Node.js
- Amazon Elastic Kubernetes Service
## Benefits

- Mental Health
- Health Insurance
- Dental Insurance
- Vision Insurance
- Life Insurance
- Parental Leave
- Paid Time Off (Pto)
- 401(k) Plans
- Employee Stock Options (ESOs)

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