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Internship Full Stack Machine Learning Engineer Jobs in Homestead, FL

Full Stack Engineer (.NET, React/Node, Python and Azure | Property Platform) Full Stack Engineer with 8-10 years in React/Node + .NET, and Azure SQL , building data-intensive apps with integrations ...

As a Full Stack Engineer, you will design, develop, and enhance applications across frontend and backend environments, working with modern engineering practices and cloud-based technologies. You will ...

DevOps Engineer

Miami, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Software Engineer

Miami, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Mobile Software Engineer

Miami, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Frontend Engineer

Miami, FL · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

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Internship Full Stack Machine Learning Engineer information

See Homestead, FL salary details

$40.9K

$123.8K

$175K

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

As of Jun 9, 2026, the average yearly pay for internship full stack machine learning engineer in Homestead, FL is $123,811.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,000.00 and $145,200.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Internship Full Stack Machine Learning Engineer, and why are they important?

To succeed as an Internship Full Stack Machine Learning Engineer, you need a solid understanding of programming (Python, JavaScript), basic machine learning concepts, and foundational knowledge in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, web development tools (React, Node.js), and version control systems like Git is typically expected. Strong problem-solving abilities, collaboration skills, and a willingness to learn set exceptional interns apart. These skills enable interns to contribute effectively to both model development and deployment, bridging the gap between data science and software engineering in real-world applications.

What is an Internship Full Stack Machine Learning Engineer?

An Internship Full Stack Machine Learning Engineer is a student or early-career professional who supports both the development of machine learning models and the integration of these models into full-stack applications. This role typically involves working on data preprocessing, building and training machine learning algorithms, and deploying these models within web or mobile applications. Interns in this field gain experience in both backend and frontend technologies, as well as in machine learning frameworks and tools. The position is ideal for those seeking hands-on experience in applying AI solutions within real-world products.

What types of projects and responsibilities can I expect as an Internship Full Stack Machine Learning Engineer?

As an Internship Full Stack Machine Learning Engineer, you can expect to work on end-to-end machine learning projects that involve both model development and integration into web or cloud applications. This may include tasks like cleaning and preparing datasets, building and testing machine learning models, developing APIs to serve predictions, and collaborating with front-end developers to deliver user-facing features. Interns often work closely with data scientists, software engineers, and product managers, gaining exposure to the full development lifecycle. These experiences help build both technical and teamwork skills, laying a strong foundation for a future career in the field.

What is the difference between Internship Full Stack Machine Learning Engineer vs Software Developer Intern?

AspectInternship Full Stack Machine Learning EngineerSoftware Developer Intern
Required SkillsKnowledge of machine learning, programming (Python, JavaScript), full stack development, data handlingProficiency in programming languages (Java, Python, JavaScript), software development, basic algorithms
Work EnvironmentCollaborates on ML models, data pipelines, backend and frontend developmentFocuses on application development, coding, debugging, and testing
Industry UsageUsed in AI-driven companies, tech startups, data science teamsCommon in software firms, app development companies, tech startups

The Internship Full Stack Machine Learning Engineer role emphasizes working with machine learning models and data-driven applications, combining full stack development skills with AI expertise. In contrast, a Software Developer Intern focuses more on traditional software development tasks like coding and debugging. Both roles are valuable entry points in tech, but they target different skill sets and project types.

What job categories do people searching Internship Full Stack Machine Learning Engineer jobs in Homestead, FL look for? The top searched job categories for Internship Full Stack Machine Learning Engineer jobs in Homestead, FL are:
Software Engineer II- Full-stack Developer

Software Engineer II- Full-stack Developer

Deloitte

Miami, FL • On-site

Other

Posted 19 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Software Engineer II, AI & Engineering/Engineering as a Service

Position Summary

Software Engineer II, AI & Engineering/Engineering as a Service
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8/1/26.

Work You'll Do

You are a hands-on full-stack developer who builds, tests, and ships reliable software as part of an agile engineering team. You contribute to the design and implementation of cloud-native applications and AI-augmented features, growing your technical depth across the stack. You will work alongside senior engineers to grow your technical skills while making meaningful contributions to our projects.

Key Responsibilities

  • Design, build, test, and maintain scalable full-stack features across front-end and back-end systems, following project engineering standards and conventions.
  • Write clean, well-documented, and maintainable code; participate in code reviews and contribute constructive technical feedback to peers.
  • Develop and maintain back-end microservices and scalable APIs; implement CI/CD pipelines, containerized workloads, and infrastructure-as-code as part of client engagements.
  • Integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI) to build intelligent, context-aware features within client applications.
  • Implement agentic AI patterns - tool-calling agents, RAG pipelines, prompt chaining, and memory management - within full-stack applications under senior engineer guidance.
  • Collaborate on prototyping and iterating AI-powered workflows and automation solutions, contributing to the practice's growing AI delivery capability.
  • Participate actively in code reviews, providing and incorporating constructive feedback.
  • Collaborate with product managers, designers, and fellow engineers to translate requirements into technical solutions.
  • Identify, diagnose, and resolve bugs and performance issues in development and production environments.
  • Assist in breaking down technical requirements into well-scoped tasks and estimates.
  • Support junior engineers through pairing, knowledge sharing, and informal mentorship.
  • Write and maintain unit, integration, and end-to-end tests to ensure software reliability.
  • Participate in on-call rotations and contribute to incident response and post-mortems.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

Qualifications

  • 4-6 years of professional software engineering experience with a focus on full-stack development.
  • 3+ years of full system lifecycle development experience, from requirements through production deployment.
  • 3+ years of hands-on full-stack experience with proficiency in at least one back-end language (Python, Java, .NET, Go, or Node.js) and a modern front-end framework (React, Angular, or Vue.js).
  • 2+ years in a client-facing development role, or a demonstrated ability to engage professionally with external stakeholders.
  • 2+ years building and consuming RESTful APIs and/or GraphQL services in a professional, team-based delivery environment.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and OOP principles.
  • Familiarity with relational or NoSQL databases and comfort writing efficient queries.
  • Working knowledge of version control systems (Git) and collaborative development workflows.
  • Understanding of testing practices and experience writing automated test suites.
  • Strong verbal and written communication skills with the ability to work effectively in a team environment.
  • Working knowledge of at least one major cloud platform (AWS, Azure, or GCP), including deployment, managed services, and basic infrastructure configuration.
  • Hands-on experience integrating at least one LLM platform or generative AI API (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, or equivalent).
  • Bachelor's degree in computer science, Engineering, or a related discipline - or equivalent professional experience.
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serv
  • Limited immigration sponsorship may be available

In addition, successful Software Engineer II candidates will have the following preferred background:

  • Experience with containerization and orchestration tools such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Experience working in an Agile/Scrum environment using tools like Jira or Linear.
  • Contributions to open-source projects or a personal portfolio demonstrating technical initiative.
  • Interest in mentoring others and taking on increased technical responsibility over time.
  • Industry-recognized cloud certifications (AWS Certified Developer, Azure Developer Associate, GCP Professional Developer, or equivalent).

Wages + Salary

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $95,600 to $188,400

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Software Engineer II, AI & Engineering/Engineering as a Service

Position Summary

Software Engineer II, AI & Engineering/Engineering as a Service
AI & Engineering leverages cutting-edge engineering capabilities to build, deploy, and operate integrated/verticalized sector solutions in software, data, AI, network, and hybrid cloud infrastructure. These solutions are powered by engineering for business advantage, transforming mission-critical operations. We enable clients to stay ahead with the latest advancements by transforming engineering teams and modernizing technology & data platforms. Our delivery models are tailored to meet each client's unique requirements.
Engineering as a Service provides complete design, implementation, and technology operations, leveraging our core engineering expertise. We transform engineering teams, modernize technology, and deliver complex programs with a product engineering approach. Our flexible delivery models-traditional teams, pools, or pods-are tailored to each client's needs, offering engineering-led advisory, implementation, and operational capabilities to accelerate innovation.

Recruiting for this role ends on 8/1/26.

Work You'll Do

You are a hands-on full-stack developer who builds, tests, and ships reliable software as part of an agile engineering team. You contribute to the design and implementation of cloud-native applications and AI-augmented features, growing your technical depth across the stack. You will work alongside senior engineers to grow your technical skills while making meaningful contributions to our projects.

Key Responsibilities

  • Design, build, test, and maintain scalable full-stack features across front-end and back-end systems, following project engineering standards and conventions.
  • Write clean, well-documented, and maintainable code; participate in code reviews and contribute constructive technical feedback to peers.
  • Develop and maintain back-end microservices and scalable APIs; implement CI/CD pipelines, containerized workloads, and infrastructure-as-code as part of client engagements.
  • Integrate LLM APIs (OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI) to build intelligent, context-aware features within client applications.
  • Implement agentic AI patterns - tool-calling agents, RAG pipelines, prompt chaining, and memory management - within full-stack applications under senior engineer guidance.
  • Collaborate on prototyping and iterating AI-powered workflows and automation solutions, contributing to the practice's growing AI delivery capability.
  • Participate actively in code reviews, providing and incorporating constructive feedback.
  • Collaborate with product managers, designers, and fellow engineers to translate requirements into technical solutions.
  • Identify, diagnose, and resolve bugs and performance issues in development and production environments.
  • Assist in breaking down technical requirements into well-scoped tasks and estimates.
  • Support junior engineers through pairing, knowledge sharing, and informal mentorship.
  • Write and maintain unit, integration, and end-to-end tests to ensure software reliability.
  • Participate in on-call rotations and contribute to incident response and post-mortems.

A successful candidate would possess these skills:

  • Ability to work independently and collaborate as part of a team
  • Effective written and verbal communication skills
  • Meticulous attention to detail and quality of work product
  • Ability to build and sustain professional relationships
  • Ability to lead projects or workstreams
  • Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
  • Strong interpersonal skills and professional demeanor
  • Ability to meet deadlines
  • Ability to provide clear guidance to others

Qualifications

  • 4-6 years of professional software engineering experience with a focus on full-stack development.
  • 3+ years of full system lifecycle development experience, from requirements through production deployment.
  • 3+ years of hands-on full-stack experience with proficiency in at least one back-end language (Python, Java, .NET, Go, or Node.js) and a modern front-end framework (React, Angular, or Vue.js).
  • 2+ years in a client-facing development role, or a demonstrated ability to engage professionally with external stakeholders.
  • 2+ years building and consuming RESTful APIs and/or GraphQL services in a professional, team-based delivery environment.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and OOP principles.
  • Familiarity with relational or NoSQL databases and comfort writing efficient queries.
  • Working knowledge of version control systems (Git) and collaborative development workflows.
  • Understanding of testing practices and experience writing automated test suites.
  • Strong verbal and written communication skills with the ability to work effectively in a team environment.
  • Working knowledge of at least one major cloud platform (AWS, Azure, or GCP), including deployment, managed services, and basic infrastructure configuration.
  • Hands-on experience integrating at least one LLM platform or generative AI API (OpenAI, Azure OpenAI, Anthropic, Google Vertex AI, or equivalent).
  • Bachelor's degree in computer science, Engineering, or a related discipline - or equivalent professional experience.
  • Ability to travel up to 50% based on the work you do and the clients and industries/sectors you serv
  • Limited immigration sponsorship may be available

In addition, successful Software Engineer II candidates will have the following preferred background:

  • Experience with containerization and orchestration tools such as Docker and Kubernetes.
  • Familiarity with CI/CD pipelines and DevOps practices.
  • Experience working in an Agile/Scrum environment using tools like Jira or Linear.
  • Contributions to open-source projects or a personal portfolio demonstrating technical initiative.
  • Interest in mentoring others and taking on increased technical responsibility over time.
  • Industry-recognized cloud certifications (AWS Certified Developer, Azure Developer Associate, GCP Professional Developer, or equivalent).

Wages + Salary

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be f...


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