1

Amazon Machine Learning Jobs in Texas (NOW HIRING)

next page

Showing results 1-20

Amazon Machine Learning information

See Texas salary details

$23.8K

$39.7K

$82K

How much do amazon machine learning jobs pay per year?

As of Aug 29, 2026, the average yearly pay for amazon machine learning in Texas is $39,673.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,300.00 and $42,900.00 per year, depending on experience, location, and employer.

What is an Amazon Machine Learning job?

An Amazon Machine Learning job involves developing, deploying, and optimizing machine learning models to improve products and services within Amazon. Professionals in this role work with large-scale data, build predictive models, and collaborate with engineering and business teams to drive data-driven decisions. Responsibilities may include data preprocessing, feature engineering, model training, and deploying machine learning solutions in production. Strong programming skills, proficiency in ML frameworks, and experience with AWS services like SageMaker are often required.

What types of projects and daily tasks can I expect in an Amazon Machine Learning position?

As an Amazon Machine Learning professional, your daily work may involve designing and deploying machine learning models, analyzing large datasets, and collaborating with cross-functional teams such as data engineers and product managers. You’ll frequently participate in code reviews, troubleshoot complex algorithms, and help optimize model performance for various Amazon products and services. Projects often range from natural language processing and recommendation systems to forecasting and computer vision initiatives. This dynamic environment offers exposure to cutting-edge innovation and opportunities to grow your technical and leadership skills within a global technology leader.

What are the key skills and qualifications needed to thrive in the Amazon Machine Learning position?

To excel in an Amazon Machine Learning role, you should possess strong expertise in machine learning algorithms, statistical analysis, programming (Python, Java, or Scala), and typically hold a degree in computer science, engineering, or a related field. Familiarity with AWS cloud services (like SageMaker, EC2, S3), big data frameworks, and relevant certifications such as AWS Certified Machine Learning are highly valuable. Effective communication, problem-solving skills, and the ability to work collaboratively in diverse teams help distinguish top candidates. These skills are crucial for developing scalable AI solutions, translating business problems into technical models, and successfully integrating them into Amazon’s large-scale operations.

What cities in Texas are hiring for Amazon Machine Learning jobs?

Cities in Texas with the most Amazon Machine Learning job openings:

Infographic showing various Amazon Machine Learning job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $39,673 per year, or $19.1 per hour.

Sr. PD Methodology Engineer, Annapurna Labs - Cloud Scale Machine Learning

Austin, TX


Amazon
IT Services • 10K+ employees

7.4

Company rating: 7.4 out of 10

Based on 7,126 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Good employer

Recommended by students

Paid breaks


$103K - $142K/yr

Full-time

Re-posted 10 days ago


Job description

Annapurna Labs (our organization within Amazon Utility Computing) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago-even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world.
Amazon provides a highly reliable, scalable, low-cost infrastructure platform in the cloud that powers hundreds of thousands of businesses in 190 countries around the world

We have data center locations in the U.S., Europe, Singapore, and Japan, and customers across all industries.
Custom SoCs (System on Chip) live at the heart of Amazon Machine Learning servers. As a member of the Cloud-Scale Machine Learning Acceleration team you'll be responsible for the design and optimization of hardware in our data centers including AWS Inferentia, Trainium Systems (our custom designed machine learning inference and training datacenter servers). Our success depends on our world-class server infrastructure; we're handling massive scale and rapid integration of emergent technologies

We're looking for an ASIC Physical Design Methodology Engineer to help us trail-blaze new technologies and architectures, while ensuring high design quality and making the right trade-offs.
Key job responsibilities
Define, develop and deploy innovative physical design and verification methodologies (RTL2GDS) for ML Accelerator chips in advanced nodes
Drive Optimizations in CAD flows/methodologies for PPA and TAT improvements
Work with EDA tool vendors to evaluate new methods, resolve bugs, improve usability.
Fine tune cloud infrastructure to improve compute and storage utilization for physical design work.
Interface directly with RTL, Physical Design, Package Design, DFT teams to improve methodologies and efficiencies.
Be able to independently troubleshoot digital tool flow usage and deploy solutions;
Fluent in scripting languages such as TCL, Python, etc. and able to build scalable and efficient flows to support parallel design developments
Create Dashboard and Central reports for project tracking and visualizing QoR/stats
A day in the life


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, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US


What Amazon employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom