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Machine Learning Evangelist Jobs (NOW HIRING)

Sr. Staff Machine Learning Engineer Overview: As a Capital One Machine Learning Engineer, you'll be ... Evangelize best practices in all aspects of the engineering and modeling lifecycles * Help recruit ...

Meta is seeking a Machine Learning SoC Architect for its Silicon Engineering organization ... Evangelize your innovative architectural solutions with your peers and leadership, while mentoring ...

Meta is seeking a Machine Learning SoC Architect for its Silicon Engineering organization ... Evangelize your innovative architectural solutions with your peers and leadership, while mentoring ...

Meta is seeking a Machine Learning SoC Architect for its Silicon Engineering organization ... Evangelize your innovative architectural solutions with your peers and leadership, while mentoring ...

... with machine learning Benefits Company Benefits Include * Health Care Plan (Medical, Dental & Vision) * Retirement Plan (401k, IRA) * Life Insurance (Basic, Voluntary & AD&D) * Paid Time Off ...

REI Systems is seeking an experienced AI Evangelist & Chief Architect to provide strategic and ... The ideal candidate combines deep technical expertise in Generative AI, machine learning ...

Work across team and discipline boundaries to evangelize ML capabilities and build them into SeatGeek's core product offerings What you have * Experience building and deploying machine learning ...

Showing results 21-40

Machine Learning Evangelist information

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How much do machine learning evangelist jobs pay per hour?

As of Sep 14, 2026, the average hourly pay for machine learning evangelist in the United States is $48.56, according to ZipRecruiter salary data. Most workers in this role earn between $48.32 and $48.80 per hour, depending on experience, location, and employer.

What is a machine learning evangelist?

A Machine Learning Evangelist is a professional who promotes the adoption and understanding of machine learning technologies within organizations and the broader tech community. They often act as a bridge between technical teams and non-technical stakeholders, helping to communicate the value and potential applications of machine learning. Their role includes giving presentations, creating educational content, advocating for best practices, and fostering a community around machine learning tools and frameworks. Ultimately, they help drive innovation and encourage the responsible use of AI and machine learning.

What skills and qualifications are needed to thrive as a machine learning evangelist?

To excel as a Machine Learning Evangelist, you need a deep understanding of machine learning concepts, programming expertise (often in Python or R), and a relevant degree in computer science or a related field. Familiarity with ML frameworks like TensorFlow or PyTorch, cloud platforms, and experience with public speaking or technical writing is highly valuable. Exceptional communication, storytelling, and networking skills help you effectively engage both technical and non-technical audiences. These skills are crucial for driving adoption, building communities, and bridging the gap between ML technology and its users.

How does a machine learning evangelist typically collaborate with technical and non-technical teams within an organization?

A Machine Learning Evangelist acts as a bridge between technical experts, such as data scientists and engineers, and non-technical stakeholders like product managers, marketing teams, and executives. They translate complex ML concepts into accessible language, advocate for adoption, and help teams understand the practical business value of machine learning solutions. This role often involves organizing workshops, presenting at conferences, and creating educational content to foster a culture of innovation and collaboration across departments.

What are popular job titles related to Machine Learning Evangelist jobs?

For Machine Learning Evangelist jobs, the most frequently searched job titles are:

Infographic showing various Machine Learning Evangelist job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $101,000 per year, or $48.6 per hour.

Delivery Consultant- AI/ML, Data & Machine Learning (DML)

Arlington, VA • On-site

Amazon
IT Services • 10K+ employees

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago


Amazon rating

7.4

Company rating: 7.4 out of 10

Based on 7,180 frontline employees who took The Breakroom Quiz


Job description

The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Machine Learning Engineer to join our team at Amazon Web Services (AWS). Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? In this role, you'll work directly with customers to design, evangelize, implement, and scale AI/ML solutions that meet their technical requirements and business objectives. You'll be a key player in driving customer success through their AI transformation journey, providing deep expertise in machine learning, generative AI, and best practices throughout the project lifecycle.
As a Machine Learning Engineer within the AWS Professional Services organization, you will be proficient in architecting complex, scalable, and secure machine learning solutions tailored to meet the specific needs of each customer. You'll help customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine tune the right models, and define paths to navigate technical or business challenges. Working closely with stakeholders, you'll assess current data infrastructure, develop proof-of-concepts, and propose effective strategies for implementing AI and generative AI solutions at scale. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
The AWS Professional Services organization is a global team of experts that help customers realize their desired business outcomes when using the AWS Cloud. We work together with customer teams and the AWS Partner Network (APN) to execute enterprise cloud computing initiatives. Our team provides a collection of offerings which help customers achieve specific outcomes related to enterprise cloud adoption. We also deliver focused guidance through our global specialty practices, which cover a variety of solutions, technologies, and industries.
This position requires that the candidate selected be a US Citizen and must currently possess and maintain an active TS/SCI security clearance.
Key job responsibilities
Designing and implementing complex, scalable, and secure AI/ML solutions on AWS tailored to customer needs, including selecting and fine-tuning appropriate models for specific use cases
Developing and deploying machine learning models and generative AI applications that solve real-world business problems, conducting experiments and optimizing for performance at scale
Collaborating with customer stakeholders to identify high-value AI/ML use cases, gather requirements, and propose effective strategies for implementing machine learning and generative AI solutions
Providing technical guidance on applying AI, machine learning, and generative AI responsibly and cost-efficiently, troubleshooting throughout project delivery and ensuring adherence to best practices
Acting as a trusted advisor to customers on the latest advancements in AI/ML, emerging technologies, and innovative approaches to leveraging diverse data sources for maximum business impact
Sharing knowledge within the organization through mentoring, training, creating reusable AI/ML artifacts, and working with team members to prototype new technologies and evaluate technical feasibility
About the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.
Why 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.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.
Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences.
Mentorship and Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
BASIC QUALIFICATIONS
- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience
- Current, active US Government Security Clearance of TS/SCI or above
- Experience in defining and creating benchmarks for assessing GenAI model performance
- Experience applying quantitative analysis to solve business problems and working on multi-team, cross-disciplinary projects
- 2+ years of computer vision experience
PREFERRED QUALIFICATIONS
- Knowledge of AWS services including compute, storage, networking, security, databases, machine learning, and serverless technologies
- Experience in performance optimization and cost management for cloud environments
- Master's degree or above in Science, Technology, Engineering, or Mathematics (STEM)
- 2+ years of cloud architecture and solution implementation experience
- Experience translating complex technical solutions and data-driven insights into clear, actionable recommendations for diverse audiences, including both technical and non-technical stakeholders
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, VA, Arlington - 131,300.00 - 177,600.00 USD annually
USA, VA, Herndon - 131,300.00 - 177,600.00 USD annually

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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, computer and electronic product manufacturing and software development

Company size

10,000+ Employees

Headquarters location

Seattle, WA, US