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Internship Machine Learning Postdoc Jobs in Plano, TX

Develop and implement machine learning and deep learning models. * Perform data preprocessing ... internships, academic projects, research, GitHub repositories, or professional experience ...

This internship provides hands-on experience applying data-driven solutions to business challenges through data analysis, reporting, visualization, machine learning, data governance, and emerging AI ...

Artificial Intelligence * Machine Learning * Data Science * Computer Engineering * Software ... AI/ML internships, research, or university projects * GitHub/portfolio demonstrating practical AI ...

AI Engineer

Dallas, TX ยท On-site

... Machine Learning, or Software Development (internships and academic projects are welcome). * Strong programming skills in Python. * Basic understanding of Machine Learning concepts and NLP.

AI Engineer

Dallas, TX ยท On-site

$96K - $132K/yr

... AI, Machine Learning, or Software Development (internships and academic projects are welcome). Strong programming skills in Python. Basic understanding of Machine Learning concepts and NLP.

Showing results 41-60

Internship Machine Learning Postdoc information

See Plano, TX salary details

$24.4K

$40.8K

$84.2K

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

As of Sep 12, 2026, the average yearly pay for internship machine learning postdoc in Plano, TX is $40,756.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,100.00 and $44,000.00 per year, depending on experience, location, and employer.

What cities near Plano, TX are hiring for Internship Machine Learning Postdoc jobs?

Cities near Plano, TX with the most Internship Machine Learning Postdoc job openings:

AI/ML Engineer

Dallas, TX โ€ข On-site

Other

This job post hasย expired today.ย Applications are no longer accepted.


Job description

AI/ML Engineer

Location: Dallas, TX, United States
Job Type: Full-Time
Experience: 0โ€“3 years
Work Authorization: OPT, H-1B, , or other valid US work authorization

Job Summary

We are seeking a motivated AI/ML Engineer to design, develop, train, and deploy machine learning and artificial intelligence solutions. The ideal candidate should have strong programming skills in Python and hands-on experience with machine learning, deep learning, data processing, and modern AI technologies.

Responsibilities
  • Develop and implement machine learning and deep learning models.
  • Perform data preprocessing, feature engineering, model training, and evaluation.
  • Build AI/ML solutions using Python and popular ML frameworks.
  • Work with structured and unstructured datasets.
  • Develop and optimize ML pipelines for model training and deployment.
  • Implement predictive models and recommendation/classification systems.
  • Work with Generative AI, LLMs, prompt engineering, or RAG-based applications.
  • Deploy and monitor ML models in cloud or production environments.
  • Collaborate with software engineers and data teams to integrate AI/ML models into applications.
  • Write clean, maintainable, and well-tested Python code.
  • Analyze model performance and improve accuracy, scalability, and efficiency.
Required Skills
  • Python
  • Machine Learning
  • Deep Learning
  • TensorFlow / PyTorch
  • Scikit-learn
  • NumPy
  • Pandas
  • SQL
  • Data Structures & Algorithms
  • Data Preprocessing & Feature Engineering
  • Model Training & Evaluation
  • REST APIs
  • Git
Preferred Skills
  • Generative AI / LLMs
  • Prompt Engineering
  • RAG
  • LangChain / LangGraph
  • NLP or Computer Vision
  • AWS / Azure / Google Cloud Platform
  • Docker
  • Kubernetes
  • MLflow
  • CI/CD
  • MLOps
  • PySpark
Education
  • Master''s degree in Computer Science, Information Technology, Artificial Intelligence, Machine Learning, Data Science, Engineering, Mathematics, or a related technical field.
  • Master''s degree preferred.
Ideal Candidate

The ideal candidate has a strong academic background in AI/ML, Computer Science, Data Science, or IT and can demonstrate hands-on experience through internships, academic projects, research, GitHub repositories, or professional experience.

entry level candidates are welcome, provided they have practical AI/ML projects and strong technical fundamentals.