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Executive Full Stack Machine Learning Engineer Jobs in Scottsdale, AZ

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Executive Full Stack Machine Learning Engineer information

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$44.8K

$135.8K

$191.9K

How much do executive full stack machine learning engineer jobs pay per year?

As of Sep 5, 2026, the average yearly pay for executive full stack machine learning engineer in Scottsdale, AZ is $135,779.00, according to ZipRecruiter salary data. Most workers in this role earn between $111,800.00 and $159,200.00 per year, depending on experience, location, and employer.

What is the difference between Executive Full Stack Machine Learning Engineer vs Data Scientist?

AspectExecutive Full Stack Machine Learning EngineerData Scientist
CredentialsBachelor's/Master's in CS, Engineering, or related; often requires experience in ML and full stack developmentBachelor's/Master's in Data Science, Statistics, or related; strong analytical and statistical skills
Work EnvironmentDevelops end-to-end ML solutions, integrates backend and frontend, collaborates with engineering teamsAnalyzes data, builds models, visualizes insights, often in research or analytics teams
Industry UsageUsed in tech companies, startups, and enterprises deploying ML productsCommon in research institutions, analytics firms, and data-driven organizations

The Executive Full Stack Machine Learning Engineer focuses on building and deploying complete ML solutions, combining software engineering and data science skills. In contrast, Data Scientists primarily analyze data and develop models without necessarily handling full stack development. Both roles require strong technical credentials but differ in scope and daily tasks.

What are popular job titles related to Executive Full Stack Machine Learning Engineer jobs in Scottsdale, AZ?

For Executive Full Stack Machine Learning Engineer jobs in Scottsdale, AZ, the most frequently searched job titles are:

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The top searched job categories for Executive Full Stack Machine Learning Engineer jobs in Scottsdale, AZ are:

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Cities near Scottsdale, AZ with the most Executive Full Stack Machine Learning Engineer job openings:

Executive Full Stack Machine Learning Engineer jobs near you
Infographic showing various Executive Full Stack Machine Learning Engineer job openings in Scottsdale, AZ as of June 2026, with employment types broken down into 96% Full Time, 1% Part Time, 2% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $135,779 per year, or $65.3 per hour.

Campus Undergraduate Full-Time Engineer - 2027 Software Engineer I, Enterprise Technology Services-

American Express

Phoenix, AZ • On-site

$78K - $124K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 4 days ago

American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

25th of 154 rated financial services

Job description


About the Team
Enterprise Technology Services teams build, operate, and modernize the technology that helps American Express deliver trusted, secure, and customer-first products and services. Software Engineers may support teams across backend engineering, frontend engineering, cloud engineering, mobile, AI/ machine learning, data-oriented engineering, infrastructure-adjacent engineering, or full-stack product development. You will design, code, test, improve, and support applications and services that help customers, colleagues, and partners get work done reliably and securely.
Responsibilities
What Type Of Work Can You Expect?
  • Develop, test, and improve software applications as part of an Agile scrum team.
  • Write clean, maintainable code; participate in code reviews; and create unit tests with guidance from experienced engineers.
  • Identify opportunities to apply new technologies, automation, and engineering practices to solve real business challenges.
  • Partner with Product Managers, Senior Engineers, Quality Engineers, Architects, and business partners to understand requirements, prioritize features, and deliver value.
  • Work across different parts of the technology stack, such as APIs, services, microservices, user interfaces, mobile experiences, cloud platforms, or data-driven solutions.
  • Explore responsible use of AI-powered developer tools, machine learning concepts, and intelligent automation relevant to your team's work.
  • Participate in graduate program learning, mentorship, networking, community, and career-development experiences while building your full-time career at American Express.

What You'll Learn
  • How software is built and delivered "the Amex Way," including structured onboarding, developer bootcamp concepts, code quality, testing, and secure engineering practices.
  • How Product, Engineering, Quality, Security, and business partners collaborate from idea to production.
  • How to translate customer or business needs into technical solutions while balancing quality, resilience, usability, and risk.
  • How to communicate progress, ask effective questions, and share technical work with both technical and non-technical partners.
  • How to grow through mentorship, feedback, technical learning, leadership exposure, and a strong graduate cohort community.

Qualifications
Minimum Qualifications
  • Must have earned a Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, or another technical field before the full-time start date.
  • Experience developing products or projects in an academic, personal, internship, research, open-source, hackathon, or professional setting.
  • Exposure to backend engineering, frontend engineering, cloud engineering, mobile engineering, AI / machine learning, data engineering, API development, or full-stack product development.
  • Familiarity with Java, JavaScript, React, TypeScript, Python, C#, Go, Kotlin, Node.js, REST APIs, SQL, Spring, or similar frameworks and tools.
  • Exposure to cloud-native development, microservices, containerization, CI/CD, DevOps, automated testing, accessibility, or secure software development concepts.
  • Interest in AI-powered development tools, generative AI, intelligent automation, responsible AI, or machine learning fundamentals.

Preferred Qualifications
  • Bachelor's degree candidates with an expected graduation date between December 2026 and June 2027.
  • Programming experience through coursework, projects, research, internships, open-source contributions, hackathons, or extracurricular activities using one or more languages such as Java, JavaScript, Python, C#, Go, Kotlin, Node.js, or similar technologies.
  • Interest in building software applications across web, mobile, backend, cloud, API, microservices, or full-stack environments.
  • Exposure to software development across backend, frontend, cloud, mobile, API, data, or full-stack environments.
  • Exposure to advanced AI software engineering concepts such as LLM integrations, prompt engineering, prompt evaluation, embeddings, retrieval-augmented generation, vector search, AI agents, agentic workflows, or human-in-the-loop review.
  • Familiarity with building or integrating AI-enabled applications using APIs, data pipelines, model inference endpoints, evaluation workflows, or cloud-based AI services.
  • Awareness of responsible AI practices, including model reliability, explainability, privacy, security, governance, bias mitigation, guardrails, and validation of AI-generated outputs.
  • Experience with modern software development practices such as version control, testing, code reviews, Agile methodologies, and collaborative development.
  • Curiosity for emerging technologies, including artificial intelligence, machine learning, developer productivity tooling, automation, and responsible AI practices.
  • Strong communication, teamwork, collaboration, learning agility, and the ability to learn emerging technologies

Technology Areas and Preferred Skills
American Express software engineers may be aligned to different technology teams based on business needs, project requirements, and individual strengths. Experience in one or more of the following areas is beneficial:
  • Back-End Engineering: Java, Python, Go, APIs, microservices, distributed systems, Big Data, or data-oriented engineering concepts.
  • Front-End Engineering: JavaScript, React, TypeScript, REST APIs, accessibility, and user experience principles.
  • Cloud Engineering: Cloud-native development, microservices, CI/CD, containerization, DevOps practices, and infrastructure-aware engineering.
  • AI & Machine Learning Engineering: Python, Java, machine learning fundamentals, AI-powered developer tools, data processing, automation, responsible AI concepts, and agentic workflow awareness.
  • Mobile Engineering: Swift, Kotlin, API integration, mobile testing frameworks, mobile architecture, and UI/UX fundamentals.
  • Core Skills Across All Areas: Problem solving, computer science fundamentals, communication, collaboration, curiosity, secure engineering, and a growth mindset.

Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and will contact qualified candidates regarding next steps.
Employment eligibility to work with American Express in the United States is required as the company will not pursue visa sponsorship for these positions.
About Us
At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service.
As part of Team Amex, you'll experience our powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express.
About the Team
We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally:
  • Competitive base salaries
  • Bonus incentives
  • 6% Company Match on retirement savings plan
  • Free financial coaching and financial well-being support
  • Comprehensive medical, dental, vision, life insurance, and disability benefits
  • Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need
  • 20+ weeks paid parental leave for all parents, regardless of gender, offered for pregnancy, adoption or surrogacy
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counseling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit our Colleague Benefits Site.
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other status protected by law. American Express will consider for employment all qualified applicants, including those with arrest or conviction records, in accordance with the requirements of applicable state and local laws, including the California Fair Chance Act, the Los Angeles County Fair Chance Ordinance for Employers, and the City of Los Angeles' Fair Chance Initiative for Hiring Ordinance. For positions covered by federal and/or state banking regulations, American Express will comply with such regulations as it relates to the consideration of applicants with criminal convictions.
We back our colleagues with the support they need to thrive, professionally and personally. That's why we have Amex Flex, our enterprise working model that provides greater flexibility to colleagues while ensuring we preserve the important aspects of our unique in-person culture. Depending on role and business needs, colleagues will either work onsite, in a hybrid model (combination of in-office and virtual days) or fully virtually.
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The below represents the expected salary range for this job requisition. Ultimately, in determining your pay, we'll consider your location, experience, and other job-related factors.

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