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Machine Learning Engineer Jobs in Boca Raton, FL

AI Engineer Location: Sunrise, FL Job Type: Contract (Long Term) Experience: 5+ years Skills ... Design and build end-to-end production AI systems integrating machine learning models, LLMs, and ...

A.I. Specialist (Intern)

Fort Lauderdale, FL · On-site

$14.25 - $19/hr

Interest and/or knowledge of programming skills in languages such as Python, Java, or C++. * Some experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn ...

Bigdata Engineer with GCP

Sunrise, FL · On-site

$109K - $131K/yr

Exposure to machine learning data pipelines * GCP certifications (e.g., Professional Data Engineer ) Education * Bachelor's or Master's degree in Computer Science, Engineering, or a related field (or ...

AI Engineer

Fort Lauderdale, FL · Remote

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Our AI solutions incorporate applications across the AI and machine learning spectrum, including ... programming experience with one of the following: Python, C++, C, CSharp, Java, Rust, or Go (or ...

FinOps Senior Site Reliability Engineer II

Boca Raton, FL · On-site

$104K - $174K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Support enterprise AI, Generative AI, and machine learning platforms. * Implement governance ... Promote engineering efficiency through reusable patterns, templates, and tooling. * Mentor ...

Posted today

Applied AI Engineer

Sunrise, FL · On-site

$100K - $150K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... machine learning models, LLMs, and supporting services into scalable applications • • ... engineering • • Experience in continuous integration/continuous deployment pipelines and ...

CTIO - AI Engineer- Senior Manager

Boca Raton, FL · On-site

$91K - $321K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

New

IT/DevOps Engineer

Fort Lauderdale, FL · On-site

$50.50 - $69/hr

HP Proliant (or equivalent) * DevOps Engineering • GitLab & Git Clients • Kubernetes • ... SQL Databases, App Insights, Stream Analytics and Machine Learning * Networking / Infrastructure ...

Senior Data Engineer

Boca Raton, FL · On-site

$100K - $136K/yr

  • Medical

  • PTO

Job Summary GeniusRx is looking for an experienced data engineer to help bring the next evolution ... Databricks for additional transformations and machine learning. * Looker for BI and reporting. You ...

Showing results 41-60

Machine Learning Engineer information

See Boca Raton, FL salary details

$29.8K

$121.8K

$183.1K

How much do machine learning engineer jobs pay per year?

As of Aug 19, 2026, the average yearly pay for machine learning engineer in Boca Raton, FL is $121,830.00, according to ZipRecruiter salary data. Most workers in this role earn between $96,000.00 and $146,600.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What does a machine learning engineer do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a machine learning engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

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

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are popular job titles related to Machine Learning Engineer jobs in Boca Raton, FL?

For Machine Learning Engineer jobs in Boca Raton, FL, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer jobs in Boca Raton, FL look for?

The top searched job categories for Machine Learning Engineer jobs in Boca Raton, FL are:

What cities near Boca Raton, FL are hiring for Machine Learning Engineer jobs?

Cities near Boca Raton, FL with the most Machine Learning Engineer job openings:

Infographic showing various Machine Learning Engineer job openings in Boca Raton, FL as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 24% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $121,830 per year, or $58.6 per hour.

Campus Graduate Masters Summer Internship Program - 2027 Software Engineer, Enterprise Technology Se

American Express

Sunrise, FL • On-site

$24.05/hr

Full-time

Posted 2 days ago

New


American Express rating

8.6

Company rating: 8.6 out of 10

Based on 37 frontline employees who took The Breakroom Quiz

23rd of 150 rated financial services


Job description


Business Unit/Role Specific Information
The Enterprise Technology Services organization partners with every part of the American Express business to power the company's growth and innovation with trust and efficiency, and drive competitive differentiation with speed. We support the delivery and operations of technology, digital, and data capabilities, platforms, and services globally. Specifically, our team is responsible for the company's technology engineering, architecture, and infrastructure, providing 24x7 support to ensure an uninterrupted, high-quality experience for customers and colleagues. We also provide product management for core enterprise platforms, and lead technology risk and information security, enterprise data governance and platforms, digital product and design, and enterprise AI platforms on behalf of the company.
At American Express, we empower future technologists to learn, innovate, and make an impact from day one. As a Software Engineer Intern, you'll join a 10-week Summer Internship Program and contribute to real-world technology projects that support seamless customer and colleague experiences. You'll build software, collaborate with Agile teams, and learn how products are designed, developed, tested, and delivered in a global enterprise environment. These skills will give you the tools to accelerate in your studies and future career!
Enterprise Technology Services teams build and operate technology that helps American Express deliver trusted, secure, and customer first products and services. Interns may be aligned to scrum teams across backend engineering, frontend engineering, cloud engineering, mobile, AI/machine learning, data oriented engineering,
or full-stack product development. The role family is Software Engineering which means designing, coding, testing, and improving applications and services that help customers, colleagues, and partners get work done reliably and securely.
Responsibilities
Responsibilities & What Type of Work to Expect?
• Discover and apply new technologies to solve real-world business challenges.
• Contribute to an Agile scrum team by developing, testing, and improving software applications.
• Write clean, maintainable code; participate in code reviews; and create unit tests with coaching from experienced engineers.
• Explore and experiment with emerging AI-powered developer tools, automation capabilities, and machine learning concepts while learning how to build software responsibly, securely, and at enterprise scale.
• Partner with Product Managers, Senior Engineers, Quality Engineers, and Architects to understand requirements, prioritize features, and deliver value.
• Build confidence working across different parts of the technology stack, such as APIs, services, microservices, user interfaces, mobile experiences, cloud platforms, or data driven solutions.
• Participate in social events, community service opportunities, learning sessions, and collaborative initiatives with fellow interns.
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 your career through mentorship, feedback, community, and continuous learning.
Qualifications
Minimum Qualifications
• Currently enrolled in a full-time graduate master's degree program
• Graduate master's degree candidates with an expected graduation date between December 2027 and June 2028.
• Demonstrated experience through coursework, projects, research, or extracurricular activities using one or more programming languages such as Java, JavaScript, Python, C#, Go, Kotlin, or similar technologies.
• Foundational understanding of computer science concepts including data structures, algorithms, object-oriented programming, debugging, and problem solving.
• Interest in building software applications across web, mobile, backend, cloud, API, or full-stack environments.
• Familiarity with modern software development practices such as version control, testing, code reviews, Agile methodologies, and collaborative development workflows.
• Curiosity and enthusiasm for emerging technologies, including artificial intelligence (AI), machine learning, intelligent automation, and AI-powered developer tools.
• Strong communication, teamwork, and collaboration skills with the ability to learn quickly, seek feedback, and work effectively in a diverse and inclusive environment.
Preferred Qualifications
• A curious, collaborative problem solver who enjoys learning new technologies and applying them to practical challenges.
• Understanding and experience leveraging AI powered development tools, generative AI, intelligent automation, responsible AI, and machine learning fundamentals.
• Ability to collaborate with Product, Engineering, Quality, Security, and business partners from idea through delivery.
• Ability to translate customer or business needs into technical solutions while balancing quality, resilience, usability, and risk.
• Strong communication skills, including the ability to share progress, ask effective questions, and explain technical work to technical and non-technical partners.
• A student who has built and programmed software through academic, personal, internship, open-source, hackathon, or project-based experiences.
• Someone who communicates clearly, welcomes feedback, and brings an inclusive, customer first mindset to team environments.
Technology Areas for Software Engineers
American Express Software Engineering Interns 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, Golang, APIs, microservices, Big Data, or Data Engineering concepts.
• Front-End Engineering: JavaScript, React, TypeScript, REST APIs, accessibility, and user experience principles.
• Cloud Engineering: Java, Python, cloud-native development, microservices, CI/CD, containerization, and DevOps practices.
• Site Reliability Engineer: Knowledge of observability tools and methodologies, including experience with logging, monitoring, tracing, and performance analysis platforms
• AI & Machine Learning Engineering: Java, Python, machine learning fundamentals, AI powered development tools, agentic workflows, AI agents, data processing, automation, and responsible AI concepts.
• Mobile Engineering: Swift, Kotlin, API integration, mobile testing frameworks, mobile architecture, and UI/UX fundamentals.
• Core Skills Across All Areas: Strong problem-solving abilities, computer science fundamentals, communication and collaboration skills, experience working in team environments, and curiosity for emerging technologies including Artificial Intelligence and Generative AI.
Our team reviews applications on a rolling basis. We appreciate your patience while we consider your application and we 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
  • Flexible work arrangements and schedules with hybrid and virtual options with Amex Flex
  • Free access to global on-site wellness centers staffed with nurses and doctors (depending on location)
  • Free and confidential counselling support through our Healthy Minds program
  • Career development and training opportunities

For a full list of Team Amex benefits, visit out 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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