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Internship Full Stack Machine Learning Engineer Jobs in Tennessee

ShyftOff

Senior Full Stack Engineer

Nashville, TN · On-site

To keep pace, we need a hands-on Full Stack Engineer who loves building scalable systems , shipping ... diving in and learning quickly.) Frontend: Vue.js, React + Next.js Backend: FastAPI Data

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Internship Full Stack Machine Learning Engineer information

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 are the most commonly searched types of Full Stack Machine Learning Engineer jobs in Tennessee? The most popular types of Full Stack Machine Learning Engineer jobs in Tennessee are:
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Internship Full Stack Machine Learning Engineer jobs near you
Cloud Engineer - Full Stack Developer

Cloud Engineer - Full Stack Developer

Innovative Solutions

Nashville, TN • On-site

Full-time

Posted 11 days ago

Job description

As a Full Stack Cloud Engineer, you’ll build and modernize scalable AWS-based applications — developing backend services, APIs, and integrations while also contributing to frontend dashboards and user interfaces. One engagement you may be migrating and refactoring a legacy application into a serverless, microservices architecture using Lambda and API Gateway, the next you’re building full-stack cloud-native applications using React, Python, or Java with secure, event-driven AWS services. You’ll collaborate closely with clients and project teams to design solutions, improve architectures, and deliver modern cloud applications that are secure, scalable, and business-driven. 

What You’ll Do:

  • Assisting in the designing and building modern and highly scalable cloud-based applications for customers
  • Migrating and modernizing customer legacy applications using AWS services
    Working with Project Managers and clients to provide recommendations and technology roadmaps to meet their business needs
  • Actively participating in team meetings and cross-functional interactions
  • Keeping team members and supervisors informed of progress and issues
  • Actively contributing to client project status meetings
  • Contributing to R&D projects to validate/invalidate new services offerings
  • Remaining current with technology trends and new technologies
  • Proposing the latest technology usage and integration standards
  • Developing and managing backend infrastructure, APIs and integrations to support cloud-based solutions, using programming languages like Python, Java, and PHP
  • Participating in code reviews, document infrastructure-as-code, and assist with UI/UX
  • Building out frontend interfaces and dashboards for applications and infrastructure using languages like Angular and React
  • Utilizing best practices for security, compliance, and business continuity in cloud solutions
 

Required Skills

  • 5+ years’ experience as a cloud engineer with hands-on expertise across AWS cloud services
  • Strong experience with infrastructure-as-code tools like CloudFormation
  • Experience coding in multiple languages including Node.js, Python, Angular, React, .NET Core, .NET Framework
  • Experience using AWS platforms including but not limited to Cognito and Amplify
  • Understanding of modern app architectures in cloud environments
  • Able to collaborate with cloud engineer and project management teams
 

Preferred

  • AWS Certification(s) a must have (can be obtained upon hire) - minimum requirement at 90 days is AWS Certified Developer Associates
  • In-depth experience with one or more programming languages like Java, JavaScript, Python, C# used for developing cloud-native applications.
  • Understanding of cloud computing concepts - IaaS, PaaS, serverless, containers etc.
  • Working knowledge of Amazon Web Services - key services like EC2, S3, Lambda, API Gateway, ECS, Fargate, RDS etc.
  • Experience using AWS command line tools and SDKs to manage infrastructure as code
  • Building, deploying, managing microservices applications on AWS
  • Working with AWS data storage solutions like DynamoDB, NoSQL, and Aurora RDS
  • Experience with containers & orchestration platforms like Docker, Kubernetes on AWS Security best practices for applications in the public cloud
  • Experience with CI/CD pipelines and automated testing
  • Building event-driven architectures on cloud platform
  • Using infrastructure as code tools like CloudFormation
  • Frontend JavaScript frameworks like React
  • Machine learning capabilities like SageMaker
  • Leveraging serverless architectures where applicable
The salary range provided is a general guideline. When extending an offer, Innovative considers factors including, but not limited to, the responsibilities of the specific role, market conditions, geographic location, as well as the candidate’s professional experience, key skills, and education/training.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.