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Machine Learning Research Intern Jobs in Frisco, TX

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Machine Learning Engineer

Addison, TX · On-site +1

$110K - $130K/yr

... Research, analyze, support, and implement machine learning solutions on the Snowflake Cloud data warehouse platform using the Snowpark framework Develop novel solutions using knowledge of the latest ...

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 ... Strong communicator who can translate complex research findings into actionable decisions for ...

Quarterhill

Machine Learning Engineer

Frisco, TX · On-site

Overview Quarterhill is seeking a Machine Learning Engineer to join our forward-thinking team ... Strong communicator who can translate complex research findings into actionable decisions for ...

Cotality

Senior Machine Learning Scientist

Dallas, TX · On-site

Research Leadership: Lead research initiatives to explore cutting-edge machine learning techniques and methodologies. * Data Analysis: Analyze large, diverse data sets to identify patterns, trends ...

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All JobsMachine Learning Research Intern JobsMachine Learning Research Intern Jobs in Frisco, TX

Machine Learning Research Intern information

See Frisco, TX salary details

$23.9K

$39.9K

$82.4K

How much do machine learning research intern jobs pay per year?

As of Aug 11, 2026, the average yearly pay for machine learning research intern in Frisco, TX is $39,855.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,400.00 and $43,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning research intern?

To thrive as a Machine Learning Research Intern, you need a strong foundation in mathematics, statistics, programming (especially Python), and an understanding of machine learning algorithms, typically supported by ongoing or completed studies in computer science or related fields. Familiarity with technical tools such as TensorFlow, PyTorch, scikit-learn, and experience with data analysis libraries are commonly required. Curiosity, problem-solving ability, and effective communication skills help interns stand out by enabling them to collaborate, share insights, and adapt to new research challenges. These skills ensure interns can contribute meaningfully to research projects, quickly learn new techniques, and effectively communicate their findings.

What are some typical challenges faced by machine learning research interns during their projects?

Machine Learning Research Interns often encounter challenges such as dealing with limited or messy datasets, tuning complex model architectures, and balancing innovative research with practical implementation. Additionally, they may need to quickly familiarize themselves with unfamiliar frameworks or tools and effectively communicate technical findings to both technical and non-technical team members. Successfully navigating these challenges can provide valuable learning experiences and help interns build strong problem-solving skills for future roles.

What does a machine learning research intern do?

A Machine Learning Research Intern assists in the development, implementation, and evaluation of machine learning models and algorithms under the supervision of experienced researchers. They often preprocess data, run experiments, analyze results, and contribute to research papers or technical reports. Interns also stay up to date with the latest advancements in machine learning, participate in team meetings, and sometimes help in coding or optimizing existing models. This role provides hands-on experience in applying theoretical knowledge to real-world problems and prepares interns for careers in AI research or development.
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Machine Learning Research Intern jobs near you
Infographic showing various Machine Learning Research Intern job openings in Frisco, TX as of August 2026, with employment types broken down into 1% As Needed, 58% Full Time, 28% Part Time, 1% Temporary, and 12% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $39,855 per year, or $19.2 per hour.

Research Scientist Intern (2025)

Whiterabbit.ai

Mckinney, TX • On-site

Other

Re-posted 21 days ago

Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity

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