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Aws Ml Jobs (NOW HIRING)

AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML ... Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over ...

Sr Solutions Architect, Annapurna ML

Cupertino, CA · On-site

$80 - $104.75/hr

AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML ... Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over ...

Sr Solutions Architect, Annapurna ML

Cupertino, CA · On-site

$80 - $104.75/hr

AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML ... Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over ...

AI/ML Engineer

Minneapolis, MN · Remote

$106K - $131K/yr

Experience with Azure/AWS ML services and enterprise-grade integrations. 9. Security & Compliance: Ensuring data privacy, scalability, and reliability of AI models in production. 10. Collaboration:

Deep expertise with AWS services, including ECS, EC2, EKS, S3, and cloud-native architectures ... ML tooling experience - Hybrid on-site requirement (McLean, VA) Thanks,

Manage and optimize cloud-based ML infrastructure (GCP Vertex AI, AWS SageMaker, or equivalent). Implement CICD pipelines for ML and AI-driven applications. Monitor, troubleshoot, and optimize model ...

Design and implement end to end machine learning ML pipelines using services such as Amazon SageMaker AWS Glue AWS Lambda and Amazon S3 Perform data collection cleaning and feature engineering to ...

New

This role sits at the intersection of ML engineering and MLOps and is core to CCT's analytics ... Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making ...

This role sits at the intersection of ML engineering and MLOps and is core to CCT's analytics ... Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making ...

This role sits at the intersection of ML engineering and MLOps and is core to CCT's analytics ... Build and maintain reproducible model training workflows on AWS (SageMaker, S3, Glue, etc.), making ...

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Aws Ml information

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How much do aws ml jobs pay per hour?

As of Jul 17, 2026, the average hourly pay for aws ml in the United States is $70.06, according to ZipRecruiter salary data. Most workers in this role earn between $62.26 and $81.73 per hour, depending on experience, location, and employer.

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

To thrive as an AWS Machine Learning (ML) Engineer, you need a solid background in machine learning algorithms, programming (Python or R), and a degree in computer science or a related field. Familiarity with AWS services like SageMaker, Lambda, and S3, as well as certifications such as AWS Certified Machine Learning – Specialty, are highly valued. Strong problem-solving, collaboration, and communication skills help you translate business needs into technical solutions and work effectively in a team. These competencies are crucial for designing scalable ML models and deploying them efficiently on AWS to drive data-driven business outcomes.

What are AWS ML engineers?

AWS ML engineers are professionals who design, build, and deploy machine learning models using Amazon Web Services (AWS) cloud platform. They utilize AWS services like SageMaker, Lambda, and EC2 to manage data, train algorithms, and scale machine learning solutions. Their expertise allows businesses to leverage AI and ML technologies efficiently and securely in the cloud.

What are some common challenges faced by AWS ML engineers when deploying machine learning models to production?

AWS ML engineers often encounter challenges such as managing model versioning, ensuring scalability, and integrating with existing data pipelines during deployment. Navigating AWS services like SageMaker for automation, monitoring, and cost optimization requires both technical skill and close collaboration with data scientists and DevOps teams. Additionally, staying updated with AWS's rapidly evolving ML toolset is essential to leverage new features and maintain efficient, secure production environments.

What is the difference between Aws Ml vs Data Scientist?

AspectAws MlData Scientist
Required CredentialsAWS certifications, programming skills (Python, SQL)Statistics, machine learning, programming (Python, R)
Work EnvironmentCloud platforms, AWS servicesData analysis, research, modeling
Industry UsageCloud-based AI/ML solutions, deploymentData analysis, predictive modeling, research

While Aws Ml specialists focus on deploying machine learning models using AWS cloud services, Data Scientists analyze data and develop models often using various tools and programming languages. Both roles require strong technical skills, but Aws Ml professionals are more cloud and deployment-oriented, whereas Data Scientists focus on data analysis and model development.

More about Aws Ml jobs
What states have the most Aws Ml jobs? States with the most job openings for Aws Ml jobs include:
Infographic showing various Aws Ml 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 $145,725 per year, or $70.1 per hour.
Sr Solutions Architect, Annapurna ML

Sr Solutions Architect, Annapurna ML

Amazon

Cupertino, CA

$80 - $104.75/hr

Full-time

Posted 14 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,974 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers


Job description

Annapurna Labs was a startup company acquired by AWS in 2015, and is now fully integrated. If AWS is an infrastructure company, then think Annapurna Labs as the infrastructure provider of AWS. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations.

AWS Nitro, ENA, EFA, Graviton and F1 EC2 Instances, AWS Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.
The Product: AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud

This is all enabled by the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. AWS Neuron and Inferentia are used at scale with customers like Anthropic, Apple, various internal Amazon teams and more customers in various other segments.
The Team: The Amazon Annapurna Labs team is a responsible for building innovation in silicon and software for 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 and verification, software and operations. Because of our teams breadth of talent, we have been able to improve AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with AWS Neuron SDK, Inferentia and Trainium ML accelerators.
You: In this customer-facing role, you will work closely with our Neuron software development team and strategic customers on accelerated Machine Learning solutions. You will bring your hands-on experience developing and deploying Deep Learning models and integrate it with our ML accelerator products, into large-scalable production applications.
You will need to be technically capable and credible in your own right, to become a trusted advisor for customers developing, deploying and scaling Deep Learning applications on AWS ML accelerators

You'll succeed in this position if you enjoy capturing and sharing best practices and insights, and help shape how AWS ML accelerator technology gets used. You will be a hands-on partner to AWS services teams, technical field communities, sales, marketing, business development, and professional services, to drive adoption. You'll leverage your communications skills, and be very technical when doing so, to help amplify the thought-leadership around AWS Neuron technology stack to the broader AWS field community, as well as our customers.
Key job responsibilities
- Design architectures and own Proof of Concept (PoC) solutions for strategic customers, leveraging AWS ML accelerators technologies and the broader set of AWS features and services.
- Drive adoption by taking ownership of technical engagements with eco-system partners and strategic customers, assisting with the definition and implementation of technical roadmaps and enabling them to successfully deploy on AWS ML Accelerator.
- Develop strong partnership with engineering organizations, serving as the customer advocate, to help drive product roadmap working backwards from customers feedback.
- Drive thought leadership by crafting and delivering compelling audience-specific messaging artifacts (product videos, demos, workshops, how to guides etc.) presenting AWS ML accelerator technology through AWS Blogs, reference architectures and solutions, and public-speaking events.
- Capture, implement and share best-practices knowledge among the AWS technical community regarding AWS ML Accelerators.
About the team
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. Our senior members enjoy one-on-one mentoring. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.


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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