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Internship Docker Developer Jobs (NOW HIRING)

Rockstar

Jr AI Engineer

Internship experience, academic work, bootcamp projects, portfolio projects, or open-source ... Familiarity with Docker, cloud environments, CI/CD concepts, or basic deployment workflows.

All Lines Technology

Software Developer

Johnstown, PA · On-site

... work, internships, or substantial personal projects * Solid understanding of data structures ... Experience with containerization (Docker) * Experience with using AI to enhance and accelerate ...

Nuclearn

Software Engineer Internship

Phoenix, AZ

$25 - $35/hr

You'll ship production code operators and engineers rely on every day. We're growing quickly ... Familiarity with Docker and containerized environments - you understand images, containers, and can ...

NuclearN AI

Software Engineer Internship

Phoenix, AZ · On-site

$25 - $35/hr

You'll ship production code operators and engineers rely on every day. We're growing quickly ... Familiarity with Docker and containerized environments - you understand images, containers, and can ...

Nuclearn

Software Engineer Internship

Phoenix, AZ · On-site

$25 - $35/hr

You'll ship production code operators and engineers rely on every day. We're growing quickly ... Familiarity with Docker and containerized environments you understand images, containers, and can ...

Aivra Health LLC

$25 - $40/hr

This internship provides hands-on experience in designing, developing, testing, and deploying ... & DevOps: * AWS * Microsoft Azure * Google Cloud Platform (Google Cloud Platform) * Docker

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Internship Docker Developer information

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How much do internship docker developer jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for internship docker developer in the United States is $22.89, according to ZipRecruiter salary data. Most workers in this role earn between $18.51 and $24.28 per hour, depending on experience, location, and employer.

What is the difference between Internship Docker Developer vs Junior DevOps Engineer?

AspectInternship Docker DeveloperJunior DevOps Engineer
Required CredentialsBasic knowledge of Docker, Linux, scriptingDocker, Linux, scripting, CI/CD tools
Work EnvironmentInternship setting, learning-focusedEntry-level professional, collaborative teams
Industry UsageTech companies, startups, training programsTech companies, cloud providers, IT firms
Search & Comparison IntentUnderstanding entry-level roles in containerizationExploring foundational DevOps positions

The Internship Docker Developer role is an entry-level position focused on learning Docker and containerization basics, often within internship programs. In contrast, a Junior DevOps Engineer involves broader responsibilities in automation, CI/CD pipelines, and infrastructure management. Both roles are suitable for those starting in tech, but the Junior DevOps Engineer typically requires more experience and skills in related tools.

More about Internship Docker Developer jobs
What cities are hiring for Internship Docker Developer jobs? Cities with the most Internship Docker Developer job openings:
What are the most commonly searched types of Docker Developer jobs? The most popular types of Docker Developer jobs are:
What states have the most Internship Docker Developer jobs? States with the most job openings for Internship Docker Developer jobs include:
What job categories do people searching Internship Docker Developer jobs look for? The top searched job categories for Internship Docker Developer jobs are:
Internship Docker Developer jobs near you
Infographic showing various Internship Docker Developer job openings in the United States as of June 2026, with employment types broken down into 93% Full Time, 1% Part Time, 1% Temporary, and 5% Contract. Highlights an 85% Physical, 1% Hybrid, and 14% Remote job distribution, with an average salary of $47,621 per year, or $22.9 per hour.
Jr AI Engineer

Jr AI Engineer

Rockstar

Remote

Full-time

Posted 27 days ago

Job description

Rockstar is recruiting for a data intelligence platform company focused on security analytics, investigations, fraud detection, and enterprise AI systems. Their team is dedicated to building production AI products that help organizations extract actionable insights from complex data. They are seeking a Jr. AI Engineer to contribute to their growing AI capabilities.
Position Summary
Our client is seeking a Jr. AI Engineer/Jr. Machine Learning Engineer to support the development, testing, and improvement of AI-powered features across their data intelligence platform. This role is designed for an early-career engineer who has strong technical fundamentals, curiosity about GenAI systems, and an interest in learning how production AI products are built and maintained.
The Jr. AI Engineer will work closely with senior engineers to assist with prompt experimentation, data preparation, RAG pipeline support, model evaluation, documentation, debugging, and basic AI service development. This role offers hands-on exposure to LLMs, embeddings, retrieval systems, ML workflows, and production engineering practices.
Essential Responsibilities
  • Assist in developing AI-powered features using Python, LLM tools, ML libraries, APIs, and internal platform services.
  • Support prompt engineering, prompt testing, model comparison, and evaluation of AI-generated outputs.
  • Help build and maintain RAG workflows, including document preparation, chunking, metadata tagging, embedding generation, retrieval testing, and result review.
  • Prepare, clean, format, and validate datasets used for model testing, prompt evaluation, and AI experiments.
  • Assist with model and workflow evaluation by reviewing outputs, identifying errors, documenting patterns, and comparing performance across approaches.
  • Write clean, readable Python code for scripts, internal tools, prototypes, experiments, and service components.
  • Support debugging of AI workflows, data pipelines, API integrations, and model behavior under the guidance of senior engineers.
  • Participate in code reviews, design discussions, team planning, and documentation efforts.
  • Learn and apply production engineering practices, including Git workflows, testing, logging, Docker, CI/CD, and deployment basics.
  • Document experiments, implementation details, findings, and recommendations clearly for technical team members.

Required Qualifications
  • 0-2 years of experience in AI engineering, machine learning, software engineering, data science, or a related technical area.
  • Internship experience, academic work, bootcamp projects, portfolio projects, or open-source contributions are acceptable.
  • Solid Python programming skills.
  • Foundational understanding of machine learning, deep learning, NLP, data processing, and model evaluation concepts.
  • Familiarity with tools or libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, pandas, NumPy, or similar technologies.
  • Interest in LLMs, GenAI systems, prompt engineering, embeddings, semantic search, RAG, and AI agents.
  • Ability to work with structured and unstructured data.
  • Comfort using Git, notebooks, command-line tools, APIs, and collaborative development workflows.
  • Strong attention to detail, curiosity, problem-solving ability, and willingness to learn from feedback.
  • Clear written communication skills for documenting technical work and experiment results.

Preferred Qualifications
  • Portfolio, academic, internship, or project experience involving LLMs, chatbots, semantic search, classification, summarization, automation, or ML workflows.
  • Exposure to vector databases, embeddings, document processing, information retrieval, or search systems.
  • Familiarity with Docker, cloud environments, CI/CD concepts, or basic deployment workflows.
  • Exposure to agent frameworks such as LangGraph, AutoGen, CrewAI, or similar tools.
  • Coursework or practical experience in machine learning, NLP, statistics, data engineering, computer science, or software engineering.
  • Interest in security analytics, investigations, data intelligence, fraud detection, or enterprise AI systems.

Special Skills or Experience Required
  • Foundational knowledge of machine learning, deep learning, NLP, LLMs, prompt engineering, and RAG concepts.
  • Solid Python skills with exposure to ML libraries such as PyTorch, TensorFlow, scikit-learn, Hugging Face Transformers, or similar tools.
  • Experience through coursework, internships, projects, or portfolio work involving AI, data preparation, model testing, search, or automation.
  • Ability to document experiments, compare model outputs, support debugging, and learn production ML practices such as Git, APIs, Docker, and CI/CD.

Success Measures
Success in this role will be measured by consistent contribution to AI experiments, clean and reliable implementation work, clear documentation, improved evaluation support, effective debugging assistance, and steady growth in production AI engineering skills. The role should help increase team capacity while developing strong internal AI engineering talent over time.

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