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Executive Aws Machine Learning Jobs (NOW HIRING)

SysMind Tech

Machine Learning

Manhattan, NY · On-site

$85/hr

Communicate findings and recommendations to stakeholders and executive leadership. Stay updated ... Azure, AWS, GCP Proven track record of successfully deploying and optimizing ML models in a ...

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Executive Aws Machine Learning information

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$26.5K

$93.6K

$184K

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

As of Jun 14, 2026, the average yearly pay for executive aws machine learning in the United States is $93,552.00, according to ZipRecruiter salary data. Most workers in this role earn between $58,000.00 and $120,500.00 per year, depending on experience, location, and employer.

What does an Executive AWS Machine Learning professional do?

An Executive AWS Machine Learning professional leads the strategic planning and implementation of machine learning solutions using Amazon Web Services (AWS) within an organization. Their responsibilities often include overseeing teams, aligning machine learning initiatives with business goals, and ensuring that scalable, secure, and cost-effective AWS-based ML services are deployed. They also stay updated on the latest AWS technologies, foster innovation, and communicate with stakeholders to drive digital transformation. This role requires a blend of technical expertise, leadership skills, and business acumen.

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

AspectExecutive Aws Machine LearningData Scientist
Required CredentialsAdvanced AWS certifications, leadership experienceStatistics, programming, data analysis degrees
Work EnvironmentLeadership roles, strategic planning, cloud infrastructureData analysis, model development, research
Employer & Industry UsageTech companies, cloud service providers, enterprisesResearch institutions, tech firms, finance, healthcare
Common Search & ComparisonYesYes

Executive Aws Machine Learning professionals focus on strategic leadership, cloud infrastructure, and overseeing ML projects within organizations, often requiring AWS certifications and leadership skills. Data Scientists primarily analyze data, develop models, and perform research to extract insights. While both roles work with machine learning, the Executive Aws Machine Learning role emphasizes management and cloud expertise, whereas Data Scientists focus on technical data analysis and model building.

What are some common challenges faced by an Executive AWS Machine Learning professional when leading cross-functional teams?

As an Executive AWS Machine Learning professional, a frequent challenge is bridging the gap between data science teams, engineering, and business stakeholders. Ensuring all teams are aligned on project goals, timelines, and technical requirements can be complex, especially when translating machine learning concepts for non-technical audiences. Additionally, managing cloud resource allocation and cost efficiency on AWS while delivering scalable ML solutions requires strategic oversight. Strong communication, project management skills, and a deep understanding of AWS services are essential to successfully lead collaborative, multidisciplinary teams.

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

To thrive as an Executive AWS Machine Learning specialist, you need deep expertise in machine learning concepts, cloud architecture, and a strong background in computer science or related fields, often supported by advanced degrees or AWS certifications. Familiarity with AWS services like SageMaker, Lambda, and data management tools, along with certifications such as AWS Certified Machine Learning – Specialty, is highly valuable. Leadership, strategic thinking, and the ability to communicate complex technical ideas to both technical and non-technical stakeholders are crucial soft skills. These skills ensure effective development and deployment of scalable ML solutions that align with business goals and drive innovation.
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What cities are hiring for Executive Aws Machine Learning jobs? Cities with the most Executive Aws Machine Learning job openings:
What are the most commonly searched types of Aws Machine Learning jobs? The most popular types of Aws Machine Learning jobs are:
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Executive Aws Machine Learning jobs near you
Infographic showing various Executive Aws Machine Learning job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 98% Full Time, and 1% Part Time. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $93,552 per year, or $45 per hour.
Software Development Manager, AWS Neuron Frameworks

Software Development Manager, AWS Neuron Frameworks

Amazon

Cupertino, CA • On-site

$152K - $201K/yr

Full-time

Posted 11 days ago

Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 6,847 frontline employees who took The Breakroom Quiz

6th of 39 rated national retailers

Job description

We're seeking a Software Development Manager to lead our Frameworks team within AWS Neuron, the software stack powering AWS Inferentia and Trainium machine learning accelerators. This role combines technical leadership, team management, and strategic open-source collaboration to shape the future of machine learning acceleration at AWS.
As the Software Development Manager, you will lead and mentor a high-performing team of software engineers while driving the development and maintenance of critical Neuron framework components. You'll drive cross-functional collaboration with compiler, runtime, and kernel development teams to ensure seamless integration of Neuron with major machine learning frameworks

You will also contribute technically by reviewing designs and implementing features.
A crucial aspect of your role will be building and nurturing strategic relationships with open-source communities, particularly with JAX, OpenXLA, and PyTorch/XLA. You'll work closely with these communities to align framework development roadmaps with Neuron's strategic objectives, ensuring our customers have access to the latest ML framework innovations.
In this role, you'll be instrumental in shaping how developers interact with AWS's machine learning accelerators, ensuring our customers can easily adopt and benefit from the latest advancements in ML frameworks. The position offers an opportunity to work at the intersection of cloud computing, machine learning, and open-source software, while leading a team that directly influences the future of ML acceleration at AWS.
The ideal candidate will bring proven experience managing software development teams and a strong background in machine learning frameworks and acceleration software

You should have a demonstrable track record of successful open-source collaboration and contributions, along with experience working with ML frameworks such as PyTorch or JAX. Excellence in cross-functional team leadership and communication is essential.
Key job responsibilities
* Responsible for the overall systems development life cycle
* Management and execution against project plans and delivery commitments
* Manage the day-to-day activities of the engineering team
* Management of resources, staffing, mentoring, and maintaining a best-of-class engineering team
* Report on status of development, quality, operations, and system performance to management.

What Amazon employees say

Pay

Benefits

Hours and flexibility

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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

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