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Amazon Machine Learning Jobs (NOW HIRING)

Senior Machine Learning Compiler Engineer

Seattle, WA

$139.40K - $183.80K/yr

Annapurna Labs Machine Learning accelerators are at the forefront of Amazon's innovation and one of several Amazon's tools used for building Generative AI on Amazon. The Inferentia chip delivers best ...

Senior Machine Learning Compiler Engineer

Seattle, WA · On-site

$139.40K - $183.80K/yr

Annapurna Labs Machine Learning accelerators are at the forefront of Amazon's innovation and one of several Amazon's tools used for building Generative AI on Amazon. The Inferentia chip delivers best ...

Senior Machine Learning Compiler Engineer

Seattle, WA

$139.40K - $183.80K/yr

Annapurna Labs Machine Learning accelerators are at the forefront of Amazon's innovation and one of several Amazon's tools used for building Generative AI on Amazon. The Inferentia chip delivers best ...

Experienced in using Amazon dockers to develop and deploy the solution * Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan ...

Experienced in using Amazon dockers to develop and deploy the solution * Proficient in JAVA & Python programming * Understanding of topic modelling, supervised & unsupervised machine learning * Plan ...

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Amazon Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do amazon machine learning jobs pay per year?

As of May 30, 2026, the average yearly pay for amazon machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 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 are the key skills and qualifications needed to thrive in the Amazon Machine Learning position, and why are they important?

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 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 cities are hiring for Amazon Machine Learning jobs? Cities with the most Amazon Machine Learning job openings:
What states have the most Amazon Machine Learning jobs? States with the most job openings for Amazon Machine Learning jobs include:
Infographic showing various Amazon Machine Learning job openings in the United States as of May 2026, with employment types broken down into 95% Full Time, 1% Part Time, 1% Contract, 2% Nights, and 1% Summer. Highlights an 100% Physical job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Software Development Engineer III, Annapurna Labs

Software Development Engineer III, Annapurna Labs

Amazon

New York, NY • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 10 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,788 frontline employees who took The Breakroom Quiz

7th of 39 rated national retailers


Job description

About the Team
The Neuroboros team was recently created to pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs' location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling.
About Amazon Annapurna Labs:
Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our AWS customers. We are at the forefront of innovation by combining cloud scale with the world's most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design, software and operations. Because of our team's breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances.
About AWS
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
About AWS Neuron:
AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it's all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks. Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.
Job Summary
You will join a dynamic team working at the cutting edge of the GenAI revolution by applying AI to AI. You will work on building agents, tools, and models to simplify and accelerate customer adoption of Neuron, the software stack supporting Amazon's Machine Learning silicon: Trainium. Partnering with external and internal customers, you will identify key obstacles and opportunities to accelerate their migration to AWS's ML silicon. You will be the technical lead for a team building AI agents and tools that simplify AWS Neuron adoption, and drive the team's vision and strategy in this space critical to AWS's Generative AI business.
Key job responsibilities
This role requires collaborating with other Neuron Software teams, Science, AWS AI Services, external partners and customers with a potential high impact on AWS's top and bottom line. As a senior member of the team applying Generative AI to accelerate Neuron adoption, you will play a key role in shaping this space with the following technical responsibilities:
- Research implementations that deliver the best possible experiences for customers.
- Deliver on goals to improve the time and effort it takes to port and optimize Machine Learning workloads on Neuron.
- Solve challenging technical problems, often ones not solved before, at every layer of the stack
- Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
- Build high-quality, highly available, always-on products.
- Potentially contribute intellectual property through patents
- Assist in the career development of others, actively mentoring individuals and the community on advanced technical issues and helping managers guide the career growth of their team members.
- Exert technical influence over the team, increasing their productivity and effectiveness by sharing your deep knowledge and experience.
BASIC QUALIFICATIONS
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Experience as a mentor, tech lead or leading an engineering team
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- Hands-on technical experience working in the Generative AI space
- Excellent written and verbal communication skills with the ability to present complex technical information concisely to executives and non-technical leaders.
- Experience in one or more of the following areas: ML compilers, production coding agents, GenAI model architecture, model training, neural network optimization, or alternatively applied math.
PREFERRED QUALIFICATIONS
- Master's degree in computer science or equivalent
- Master's degree or above in computer science or equivalent
- 2+ years in machine learning or other computational modeling environments with an emphasis on hosting, building or optimizing models for diverse hardware platforms
- Proven track record in building AI agents that automate ML workload optimization, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimization
- Experience working with open-source software communities in the optimization space or related areas
- Domain-level knowledge of AWS services
- Knowledge of the state-of-the-art technology used in the Machine Learning space and its mathematical underpinning
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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, NY, New York - 184,900.00 - 250,200.00 USD annually

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About Amazon

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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