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Machine Learning Intern Jobs in Coppell, TX (NOW HIRING)

Black Box

AI Intern - Dallas, TX

Plano, TX · On-site

AI Engineer Intern - AI Center of Excellence (CoE) Location: Plano, Texas, USA Internship Duration ... Prior experience must include applied AI / Machine Learning , with hands-on exposure to Generative ...

PNC Bank

Technology Undergraduate Intern

Dallas, TX

$18 - $35/hr

Past example internship projects include machine learning development, automating current manual ... Participates as an intern in the PNC summer internship program. * Performs or assists with the core ...

Copart, Inc

DevOps Engineering Intern

Dallas, TX · On-site

Position Overview We are seeking a motivated DevOps Intern to support the deployment, automation ... AI / MLOps Support * Assist with deployment and monitoring of machine learning and AI applications.

Copart, Inc.

DevOps Engineering Intern

Dallas, TX · On-site

Position Overview We are seeking a motivated DevOps Intern to support the deployment, automation ... AI / MLOps Support * Assist with deployment and monitoring of machine learning and AI applications.

Ericsson

Integration Engineer - Intern

Plano, TX · On-site

As an Integration Engineer Intern, you'll play an essential role in ensuring seamless software and infrastructure integration, working with AI-enabled tools and machine learning pipelines that ...

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All JobsMachine Learning Intern JobsMachine Learning Intern Jobs in Coppell, TX

Machine Learning Intern information

See Coppell, TX salary details

$23.5K

$39.3K

$81.2K

How much do machine learning intern jobs pay per year?

As of Aug 16, 2026, the average yearly pay for machine learning intern in Coppell, TX is $39,312.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,000.00 and $42,500.00 per year, depending on experience, location, and employer.

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

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

More about Machine Learning Intern jobs

What are the most commonly searched types of Machine Learning jobs in Coppell, TX?

The most popular types of Machine Learning jobs in Coppell, TX are:

What job categories do people searching Machine Learning Intern jobs in Coppell, TX look for?

The top searched job categories for Machine Learning Intern jobs in Coppell, TX are:

What cities near Coppell, TX are hiring for Machine Learning Intern jobs?

Cities near Coppell, TX with the most Machine Learning Intern job openings:

Machine Learning Intern jobs near you
Infographic showing various Machine Learning Intern job openings in Coppell, TX as of August 2026, with employment types broken down into 14% Internship, 28% Full Time, 29% Part Time, and 29% Temporary. Highlights an 100% In-person job distribution, with an average salary of $39,312 per year, or $18.9 per hour.

AI Intern - Dallas, TX

Black Box

Plano, TX • On-site

Part-time

Re-posted 19 days ago

Job description


AI Engineer Intern - AI Center of Excellence (CoE)
Location: Plano, Texas, USA
Internship Duration: 6-12 months (12 months preferred)
Company: Black Box
Eligibility: Master's students with at least 6 months remaining before graduation and prior professional experience in applied AI
Company Overview
Black Box Network Services is a leading global communications system integrator specializing in designing, sourcing, implementing, and managing complex technology solutions. As part of our strategic transformation, Black Box is expanding its AI Center of Excellence (CoE) to deliver enterprise-grade AI solutions across multiple business domains.
The AI CoE focuses on building scalable, secure, and production-ready AI systems, establishing best practices for enterprise AI adoption, and integrating AI capabilities into core business platforms.
Role Summary
As an AI Engineer Intern in the AI Center of Excellence (CoE), you will contribute to the design, development, and integration of applied AI solutions using pre-trained Large Language Models (LLMs), traditional machine learning techniques, and deterministic approaches.
This role offers hands-on experience building enterprise-grade Generative AI solutions across backend services, data pipelines, orchestration, and user-facing applications. Working closely with experienced AI engineers, you will contribute to real-world AI use cases integrated with platforms such as ServiceNow, SAP, Salesforce, and Azure services.
This internship is designed to strengthen applied AI engineering skills and prepare candidates for conversion into a full-time AI Engineer role.
Eligibility Requirements
  • Currently pursuing a Master's degree in Engineering or a related field (Computer Science, Artificial Intelligence, Data Science, or similar).
  • Must have at least 6 months remaining to complete the Master's program at the time of joining.
  • Must have a minimum of 2 years of relevant professional experience between Bachelor's and Master's programs.
  • Prior experience must include applied AI / Machine Learning, with hands-on exposure to Generative AI use cases.
  • Available for a full-time, on-site internship for a minimum of 6-12 months (depending on academic program constraints).

Key Responsibilities AI & Generative AI Development
  • Build and integrate AI solutions using pre-trained LLMs for conversational AI, summarization, and enterprise knowledge retrieval.
  • Implement RAG-based architectures connecting LLMs with structured and unstructured enterprise data.
  • Develop and test AI agents, traditional ML models, and deterministic logic for real-world use cases.
  • Contribute to AI orchestration using LangChain and workflow automation using n8n.

Full-Stack & Enterprise Integration
  • Build AI-enabled user interfaces and integrate them with backend services.
  • Develop and maintain backend APIs and services.
  • Integrate AI solutions with enterprise platforms such as ServiceNow, SAP, Salesforce, and Azure services.

Data, Testing & Deployment
  • Build and maintain data pipelines, including preprocessing and quality checks.
  • Support testing, debugging, deployment, and monitoring of AI services on Azure.
  • Document AI workflows, integrations, and solution lifecycle updates.

Learning & Collaboration
  • Collaborate with AI, data, and platform teams to deliver production-ready AI solutions.
  • Continuously learn and apply best practices in Generative AI, RAG patterns, and enterprise AI systems.

Required Technical Skills
  • Programming: Strong working knowledge of Python.
  • Applied AI / GenAI: Hands-on experience building or integrating ML or Generative AI solutions.
  • Generative AI: Practical experience with LLMs, prompt engineering, and/or RAG-based architectures.
  • Backend Development: Experience building APIs using FastAPI, Flask, or Node.js (TypeScript).
  • Frontend Development: Working experience building React-based user interfaces and integrating them with backend APIs.
  • Data Handling: Experience working with structured and unstructured data, including basic preprocessing or ETL.
  • APIs & Cloud: Experience consuming REST APIs and familiarity with cloud platforms (Azure preferred).

Required Prior Professional Experience
  • 2+ years of relevant professional experience between Bachelor's and Master's programs.
  • Experience in applied AI, machine learning, or software engineering with AI components.
  • Ability to translate AI concepts into working prototypes or production-ready solutions.

Required Soft Skills
  • Strong learning mindset, ownership, and clear communication with a structured problem-solving approach.

Preferred Skills / Experience
  • Familiarity with NLP concepts and foundational Generative AI models.
  • Awareness of responsible AI and basic AI governance concepts.
  • Exposure to Microsoft Power Platform or low-code automation tools.

About Black Box
Black Box is a leading technology solutions provider focused on accelerating customer success through innovation, ownership, transparency, and collaboration. With over 2,500 team members across 24 countries, Black Box delivers high-value solutions globally and is a wholly-owned subsidiary of AGC Networks. Black Box is an equal opportunity employer.

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