1

Aws Machine Learning Engineer Jobs (NOW HIRING)

Applied Machine Learning Engineer | Music Software (Multiple Roles open) Role: Applied Machine ... AWS cloud environment for deploying and scaling ML solutions. • Ability to preprocess and model ...

The Machine Learning Engineer will leverage their strong technical background and knowledge to ... Manage and deploy cloud-based ML services across major cloud computing environments, including AWS ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

Familiarity with cloud-based platforms for machine learning (e.g., AWS, Google Cloud, Azure) * Strong problem-solving skills and analytical thinking REQUIRED SKILLS * Proficiency in programming ...

We are seeking an MLOps Engineer to build, deploy, and optimize machine learning infrastructure ... AWS MLOps (SageMaker, Lambda, Step Functions, S3) * Python * CI/CD Pipelines for Machine Learning ...

next page

Showing results 1-20

Aws Machine Learning Engineer information

See salary details

$31.5K

$128.8K

$193.5K

How much do aws machine learning engineer jobs pay per year?

As of Jul 11, 2026, the average yearly pay for aws machine learning engineer in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an AWS Machine Learning Engineer, and why are they important?

To thrive as an AWS Machine Learning Engineer, you need strong proficiency in machine learning algorithms, programming languages like Python, and a solid understanding of cloud architecture, typically supported by a degree in computer science or a related field. Familiarity with AWS services such as SageMaker, Lambda, and S3, as well as relevant certifications like AWS Certified Machine Learning – Specialty, is highly valuable. Strong problem-solving, collaboration, and communication skills set top performers apart in this role. These skills ensure successful design, deployment, and optimization of scalable machine learning solutions on AWS that meet business needs.

What are AWS Machine Learning Engineers?

AWS Machine Learning Engineers are specialized professionals who design, build, deploy, and manage machine learning models using Amazon Web Services (AWS) cloud infrastructure. They leverage AWS tools and services, such as SageMaker, to create scalable and efficient machine learning solutions for businesses. Their responsibilities include data preparation, model training, optimization, deployment, and monitoring in a cloud environment. AWS Machine Learning Engineers often collaborate with data scientists, software engineers, and DevOps teams to integrate machine learning models into production systems.

How does an AWS Machine Learning Engineer typically collaborate with data scientists and DevOps teams?

As an AWS Machine Learning Engineer, you’ll work closely with data scientists to operationalize models, ensuring they are scalable and production-ready on AWS platforms. You’ll also frequently collaborate with DevOps teams to automate deployment pipelines, monitor model performance, and manage infrastructure using AWS services like SageMaker, Lambda, and CloudFormation. This cross-functional teamwork is essential for maintaining reliable, efficient ML workflows and for quickly resolving issues that arise in live environments.

What is the difference between Aws Machine Learning Engineer vs Data Scientist?

AspectAws Machine Learning EngineerData Scientist
CredentialsAWS certifications, machine learning coursesStatistics, data analysis, programming skills
Work EnvironmentCloud platforms, AWS services, deployment pipelinesData analysis, modeling, research environments
Industry UsageTech, finance, healthcare using AWS for ML solutionsResearch, analytics, business intelligence
Search/Comparison IntentFocus on cloud-based ML deployment and engineeringFocus on data analysis and modeling

While both roles involve working with data and machine learning, Aws Machine Learning Engineers specialize in deploying ML models on AWS cloud platforms, focusing on infrastructure and scalable solutions. Data Scientists primarily analyze data, build models, and generate insights, often using a variety of tools and programming languages. The roles overlap in skills but differ in their primary focus and work environment.

More about Aws Machine Learning Engineer jobs
What states have the most Aws Machine Learning Engineer jobs? States with the most job openings for Aws Machine Learning Engineer jobs include:
Infographic showing various Aws Machine Learning Engineer job openings in the United States as of July 2026, with employment types broken down into 94% Full Time, 2% Part Time, and 4% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $128,769 per year, or $61.9 per hour.
Sr. DFT Design Engineer, AWS Machine Learning Acceleration

Sr. DFT Design Engineer, AWS Machine Learning Acceleration

Amazon

Austin, TX

$103K - $142K/yr

Full-time

Re-posted 29 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,956 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Custom SoCs (System on Chip) are at the heart of AWS Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team, you'll be responsible for designing and optimizing hardware in our data centers, including AWS Inferentia and Trainium systems-our custom-designed machine learning inference and training servers. Our success depends on world-class server infrastructure as we handle massive scale and rapidly integrate emerging technologies.

We're looking for a Sr. DFT Design Engineer to help us trailblaze new technologies and architectures while ensuring high design quality and making the right trade-offs.
Key job responsibilities
Define and develop state-of-the-art Design for Test (DFT) architectures for advanced technology nodes
Work closely with block designers and physical design (PD) team to implement highly efficient DFT solutions
Act as the primary point of contact for cross-functional stakeholders (PD, Architecture, and Product Engineering) to align schedules and goals
Mentor and develop junior engineers through code reviews, methodology training, and technical guidance
Manage project timelines and deliverables, ensuring high-quality DFT implementation from RTL through Silicon bring-up
.


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Amazon logo

About Amazon

Sourced by ZipRecruiter

Amazon.com, Inc., commonly known as Amazon, is an American multinational technology company. It was founded by Jeff Bezos in 1994 and initially started as an online marketplace for books. Since then, Amazon has expanded its operations and become one of the largest e-commerce companies in the world. Amazon's primary business is its online retail platform, where customers can purchase a vast array of products, including electronics, clothing, books, home goods, and much more. The company offers a convenient and user-friendly shopping experience, with features such as fast shipping, customer reviews, and personalized recommendations. In addition to its e-commerce platform, Amazon has diversified its business into various other areas. One of its notable ventures is Amazon Web Services (AWS), a comprehensive cloud computing platform that provides services such as storage, compute power, and database management to individuals and businesses. AWS has become a leader in the cloud computing industry, powering many websites and applications worldwide. Amazon has also developed its own consumer electronics, including the popular Amazon Kindle e-reader, Fire tablets, Fire TV streaming devices, and the Alexa-powered Echo smart speakers. The Alexa voice assistant, integrated into these devices, allows users to interact with their devices using voice commands, perform tasks, and access information. Furthermore, Amazon has expanded into media and entertainment. It operates Prime Video, a streaming service that offers a wide range of movies, TV shows, and original content. Amazon Music provides a platform for streaming and purchasing digital music, while Audible offers audiobooks and other audio content. The company's commitment to customer satisfaction and convenience is demonstrated by its membership program, Amazon Prime. Prime members receive various benefits, including free two-day shipping, access to streaming services, exclusive deals, and more.

Industry

It services, book publishers, retail, real estate and computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US