Senior MLE, CreativeFlux, AI Studios
Amazon (AWS)hyperscaler
New York, New York, USA · Sunnyvale, California, USA · senior · full time
Apply at Amazon (AWS) ↗original posting on www.amazon.jobs
posted today · first seen today · verified today
Hardwaregpu-genericnvidia
Infra layerml-platformtraining-frameworksscheduling-orchestrationinference-engines
Skills & stackpython-langkubernetes-opsmodel-parallelismobservabilitytensorrt-stackquantizationcuda
Workload stageinferencefine-tuningdistributed-inference
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
Build and operate ML training and serving infrastructure for the CreativeFlux platform. Strong hands-on experience with EKS / Kubernetes is required.
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
Contribute to 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 where they move team metrics
A day in the life
As an MLE on the AI Studios team, you'll spend most of your time deploying and tuning generative ML models, optimizing inference pipelines, and building the EKS infrastructure that lets Applied Scientists move new architectures into production. A typical day might include scaling a video generation endpoint to handle a production deadline, debugging a multi-GPU training job that's checkpointing too slowly, or working with a Scientist to take a new image model from a research notebook to a serving fleet. You'll work with other Nara platform teams who owns other building blocks, making sure ML capabilities land cleanly in the workflows artists actually use. You'll participate in team standups, model review sessions, on-call rotations, and platform-wide design reviews with the other Nara teams. You'll learn from experienced engineers and scientists and gradually take on more complex challenges as you grow.
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.
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
Build and operate ML training and serving infrastructure for the CreativeFlux platform. Strong hands-on experience with EKS / Kubernetes is required.
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
Contribute to 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 where they move team metrics
A day in the life
As an MLE on the AI Studios team, you'll spend most of your time deploying and tuning generative ML models, optimizing inference pipelines, and building the EKS infrastructure that lets Applied Scientists move new architectures into production. A typical day might include scaling a video generation endpoint to handle a production deadline, debugging a multi-GPU training job that's checkpointing too slowly, or working with a Scientist to take a new image model from a research notebook to a serving fleet. You'll work with other Nara platform teams who owns other building blocks, making sure ML capabilities land cleanly in the workflows artists actually use. You'll participate in team standups, model review sessions, on-call rotations, and platform-wide design reviews with the other Nara teams. You'll learn from experienced engineers and scientists and gradually take on more complex challenges as you grow.
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
- 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.
USA, CA, Sunnyvale - 193,300.00 - 261,500.00 USD annually
USA, NY, New York - 184,900.00 - 250,200.00 USD annually
- 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, Sunnyvale - 193,300.00 - 261,500.00 USD annually
USA, NY, New York - 184,900.00 - 250,200.00 USD annually