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Internship Machine Learning Engineer Jobs in Arlington, TX

UNAVAILABLE

Machine Learning Engineer

Frisco, TX · On-site

$140 - $190/hr

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems . In this role, you will design ...

Confie

Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... machine learning models and algorithms that will improve Confie's business outcome/customer experience Perform data cleansing, analysis, and feature engineering using Python Ability to work with ...

Pluralsight, LLC

Machine Learning Engineer

Westlake, TX · On-site

$160K/yr

A Machine Learning Engineer helps our learners discover content that is relevant to their interests and goals, providing them with experiences tailored just to their needs, and ensure they are ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Capital One

Lead Machine Learning Engineer

Plano, TX · On-site

$98K - $129K/yr

Lead Machine Learning Engineer As a Capital One Lead Machine Learning Engineer (MLE), you'll be ... Internship experience does not apply) * At least 4 years of experience programming with Python ...

Yum

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Yum Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Yum! Brands

Machine Learning Engineer II

Plano, TX · On-site

As a Machine Learning Engineer, you will play a crucial role in developing and deploying cutting-edge machine learning models and solutions to enhance various aspects of our business operations, from ...

Tiger Analytics

Machine Learning Engineer

Plano, TX · On-site

$120 - $150/hr

Overview Tiger Analytics is looking for experienced Machine Learning Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in ...

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All JobsMachine Learning Engineer JobsInternship Machine Learning Engineer JobsInternship Machine Learning Engineer Jobs in Arlington, TX

Internship Machine Learning Engineer information

See Arlington, TX salary details

$22.9K

$38.3K

$79.2K

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

As of Aug 11, 2026, the average yearly pay for internship machine learning engineer in Arlington, TX is $38,323.00, according to ZipRecruiter salary data. Most workers in this role earn between $29,200.00 and $41,400.00 per year, depending on experience, location, and employer.

What does an internship machine learning engineer do?

An Internship Machine Learning Engineer works alongside experienced engineers to help develop, test, and deploy machine learning models. Their responsibilities may include cleaning and preparing data, writing code for model training, evaluating model performance, and contributing to research tasks. Interns often learn to use popular frameworks such as TensorFlow or PyTorch and gain hands-on experience with real-world datasets. This role is designed to help students or recent graduates apply their academic knowledge to practical problems while developing industry-relevant skills.

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

AspectInternship Machine Learning EngineerData Scientist Intern
Required CredentialsBasic programming, introductory ML knowledgeStatistics, data analysis, programming
Work EnvironmentDeveloping ML models, coding, testingData analysis, visualization, reporting
Employer & Industry UsageTech companies, startups, AI firmsTech, finance, healthcare, consulting

Internship Machine Learning Engineers focus on developing and testing machine learning models, often requiring programming and basic ML knowledge. Data Scientist Interns analyze data, create visualizations, and generate insights. Both roles are common in tech and data-driven industries, but ML Engineer internships emphasize model deployment, while Data Science internships focus on data analysis and reporting.

What types of projects and responsibilities can I expect as an internship machine learning engineer?

As an Internship Machine Learning Engineer, you will typically support the development, testing, and deployment of machine learning models under the guidance of senior engineers. Your responsibilities may include data preprocessing, exploratory data analysis, implementing algorithms, and evaluating model performance. You'll often collaborate closely with data scientists, software engineers, and product managers, gaining exposure to real-world workflows and tools. This hands-on experience is invaluable for building technical skills and understanding how machine learning solutions are integrated into larger products.

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

To excel as an Internship Machine Learning Engineer, you typically need a solid background in mathematics, programming (especially Python), and foundational machine learning concepts, often supported by coursework or relevant project experience. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is common, along with proficiency in data processing libraries. Curiosity, strong problem-solving abilities, and effective teamwork and communication skills help set candidates apart. These competencies ensure you can contribute meaningfully to projects, adapt to new challenges, and collaborate productively in a rapidly evolving technical environment.
What are the most commonly searched types of Machine Learning Engineer jobs in Arlington, TX? The most popular types of Machine Learning Engineer jobs in Arlington, TX are:
What cities near Arlington, TX are hiring for Internship Machine Learning Engineer jobs? Cities near Arlington, TX with the most Internship Machine Learning Engineer job openings:
Internship Machine Learning Engineer jobs near you

Machine Learning Engineer

UNAVAILABLE

Frisco, TX • On-site

$140 - $190/hr

Other

Posted 6 days ago

Job description

Overview

Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team building the next generation of Intelligent Transportation Systems. In this role, you will design, develop, and deploy state-of-the-art computer vision and language models that power scalable, real-world solutions. You’ll work with large-scale image and video data, building and optimizing production-grade vision systems while contributing clean and modular code to shared repositories.

As part of our AI team, you’ll collaborate closely with engineering teams to deliver high-impact features for our growing SaaS platform. The ideal candidate brings hands‑on experience deploying computer vision and language models in production and applying MLOps best practices on cloud platforms.

Responsibilities
  • Fine‑tune and deploy computer vision and deep learning models for object detection, object tracking, and OCR at scale.
  • Develop vision‑language models and Mixture of Experts architectures, from experimental design through production deployment.
  • Architect Retrieval‑Augmented Generation (RAG) systems, including vector store design, hybrid search strategies, chunking pipelines, and context relevance evaluation.
  • Apply MLOps best practices for training, evaluation, deployment, and monitoring of production grade computer vision models, with an emphasis on clean, modular, maintainable code.
  • Contribute to our machine learning repositories and optimize models for performance, scalability, and real‑time inference across edge and cloud environments.
  • Drive performance optimization and scalability of ML systems across edge and cloud environments.
  • Collaborate with cross‑functional teams to integrate computer vision solutions into end‑to‑end products, translating research outcomes into measurable platform impact.

This list of responsibilities might not cover everything you'll end up doing.

Qualifications
  • 5+ years of hands‑on machine learning experience, with deep specialization in computer vision and a proven track record of shipping models to production.
  • Master's degree required (Ph.D. preferred) in Computer Science, Machine Learning, or a closely related field.
  • Extensive knowledge of computer vision architectures such as Vision Transformers and VLMs along with OpenCV and PIL.
  • Experience with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes) able to own the full model lifecycle from experimentation through production monitoring.
  • Experience building and deploying LLM-based systems and Retrieval‑Augmented Generation (RAG) pipelines, including vector store integration and retrieval evaluation.
  • Strong communicator who can translate complex research findings into actionable decisions for engineering and product stakeholders.
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