Machine Learning Engineer II, AWS Just-Walk-Out Science Team
Amazon
Full-time
On-site
Seattle, Washington, United States
$129,300 - $223,600 USD yearly
AI and Machine Learning
As part of the AWS Solutions organization, we're advancing the frontier of visual reasoning and agentic AI technologies. Our vision is to develop sophisticated AI systems that can understand, interpret, and reason about visual information at human-like levels, enabling breakthrough applications across multiple industries.
The Team
Our team is pioneering new approaches to visual reasoning that combine advanced computer vision, multi-modal AI, and agentic architectures. We're tackling fundamental challenges in how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing novel techniques for efficient visual processing that can scale to enterprise requirements.
Key job responsibilities
- Research and implement advanced visual reasoning architectures that can understand complex spatial relationships and temporal dynamics
- Develop novel approaches to token compression and memory management for processing continuous visual streams
- Collaborate with Scientists to enhance multi-modal language models for improved visual understanding and reasoning capabilities
- Design and optimize distributed training systems for large-scale visual AI models
- Build efficient inference pipelines that can process multiple visual streams within strict resource constraints
- Implement hybrid edge-cloud architectures for deploying visual reasoning systems at scale.
A day in the life
As an MLE on our team, you'll be at the forefront of developing next-generation visual reasoning systems. You'll tackle challenges like designing efficient architectures for processing visual information, implementing sophisticated memory management for long-term reasoning, and developing novel approaches to maintain AI capabilities while optimizing for real-world constraints. You'll collaborate closely with Applied Scientists to advance the state-of-the-art while ensuring our solutions meet rigorous requirements for accuracy, latency, and cost.
About the team
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign opportunities based on what will help each team member develop into a better-rounded contributor.
- 3+ years of non-internship professional software development experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
- Proficient in Python or related language.
- Hands-on model training experience in PyTorch and deep learning frameworks such as MMEngine or Megatron-LM; experienced in large-scale deep learning or machine learning operations.
- Familiar with modern visual-language models, multi-modal AI systems, pre-training and post-training techniques. Proficient in training profilers and performance analysis tools to identify and optimize bottlenecks in model training.
- Master's or PhD degree in computer science or equivalent.
- 1+ years of experience in developing, deploying or optimizing ML models. Exceptional engineering skills in building, testing, and maintaining scalable distributed GPU training frameworks. Familiar with HuggingFace Transformers for vision-language modeling.
- Hands-on experience in large-scale multimodal LLM and generative model training. Contributions to popular open-source LLM frameworks or research publications in top-tier AI conferences, such as CVPR, ECCV, ICCV, ICLR, etc.
- Experience in GPU utilization and memory optimization techniques like kernel fusion and custom kernels, mixed precision training using lower precision and dynamic loss scaling, gradient (activation) checkpointing, gradient accumulation, offloading optimizer states, and smart prefetching, Fully Sharded Data Parallel (FSDP), tensor and pipeline model parallelism.
- Proven experience in large-scale video understanding tasks, with a focus on multi-modal learning that integrates visual and/or textual information; includes experience designing efficient data preprocessing pipelines, building and scaling multi-modal model architectures, and conducting robust evaluation at scale.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Team
Our team is pioneering new approaches to visual reasoning that combine advanced computer vision, multi-modal AI, and agentic architectures. We're tackling fundamental challenges in how AI systems understand spatial relationships, reason about object interactions, and maintain contextual awareness across time. Working at the intersection of computer vision and large language models, we're developing novel techniques for efficient visual processing that can scale to enterprise requirements.
Key job responsibilities
- Research and implement advanced visual reasoning architectures that can understand complex spatial relationships and temporal dynamics
- Develop novel approaches to token compression and memory management for processing continuous visual streams
- Collaborate with Scientists to enhance multi-modal language models for improved visual understanding and reasoning capabilities
- Design and optimize distributed training systems for large-scale visual AI models
- Build efficient inference pipelines that can process multiple visual streams within strict resource constraints
- Implement hybrid edge-cloud architectures for deploying visual reasoning systems at scale.
A day in the life
As an MLE on our team, you'll be at the forefront of developing next-generation visual reasoning systems. You'll tackle challenges like designing efficient architectures for processing visual information, implementing sophisticated memory management for long-term reasoning, and developing novel approaches to maintain AI capabilities while optimizing for real-world constraints. You'll collaborate closely with Applied Scientists to advance the state-of-the-art while ensuring our solutions meet rigorous requirements for accuracy, latency, and cost.
About the team
Inclusive Team Culture
Here at Amazon, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.
Work/Life Balance
Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.
Mentorship & Career Growth
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign opportunities based on what will help each team member develop into a better-rounded contributor.
- 3+ years of non-internship professional software development experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience.
- Proficient in Python or related language.
- Hands-on model training experience in PyTorch and deep learning frameworks such as MMEngine or Megatron-LM; experienced in large-scale deep learning or machine learning operations.
- Familiar with modern visual-language models, multi-modal AI systems, pre-training and post-training techniques. Proficient in training profilers and performance analysis tools to identify and optimize bottlenecks in model training.
- Master's or PhD degree in computer science or equivalent.
- 1+ years of experience in developing, deploying or optimizing ML models. Exceptional engineering skills in building, testing, and maintaining scalable distributed GPU training frameworks. Familiar with HuggingFace Transformers for vision-language modeling.
- Hands-on experience in large-scale multimodal LLM and generative model training. Contributions to popular open-source LLM frameworks or research publications in top-tier AI conferences, such as CVPR, ECCV, ICCV, ICLR, etc.
- Experience in GPU utilization and memory optimization techniques like kernel fusion and custom kernels, mixed precision training using lower precision and dynamic loss scaling, gradient (activation) checkpointing, gradient accumulation, offloading optimizer states, and smart prefetching, Fully Sharded Data Parallel (FSDP), tensor and pipeline model parallelism.
- Proven experience in large-scale video understanding tasks, with a focus on multi-modal learning that integrates visual and/or textual information; includes experience designing efficient data preprocessing pipelines, building and scaling multi-modal model architectures, and conducting robust evaluation at scale.
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.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.