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Machine Learning Engineer Intern Jobs in Houston, TX

Senior Machine Learning Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must-Have (Technical Expertise & Core Responsibilities) * Deep Neural Networks (DNN): * Hands-on ...

The Principal Machine Learning Engineer will define the vision for AI across platforms, lead the lifecycle of large-scale foundation models, and collaborate with various teams to ensure alignment ...

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Senior/Principal Machine Learning Engineer 200-300k Remote position possible Description * Develop solutions for autonomous driving, from experimentation to full commercialization. * Explore new ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

Mechanical Engineer Intern

Houston, TX ยท On-site

$18 - $24/hr

The Mechanical Engineer Intern will support our Quality and Aftermarket Sales teams. This is a ... Learning Opportunities: * Hands-on experience with metal fabrication and water control products.

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... Engineer Intern to support the development of internal tools, automation workflows, and ... This role is ideal for someone who enjoys solving complex problems, learning quickly, and ...

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Senior AI Engineer

Houston, TX ยท On-site

$99K - $137K/yr

Design, develop, and deploy advanced AI and machine learning models to solve complex business ... Mentor junior engineers and provide technical guidance on AI best practices, model development, and ...

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Machine Learning Engineer Intern information

See Houston, TX salary details

$24.4K

$40.7K

$84K

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

As of Jul 1, 2026, the average yearly pay for machine learning engineer intern in Houston, TX is $40,666.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,000.00 and $43,900.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What is a Machine Learning Engineer Intern job?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

What are the most commonly searched types of Machine Learning Engineer jobs in Houston, TX? The most popular types of Machine Learning Engineer jobs in Houston, TX are:
What job categories do people searching Machine Learning Engineer Intern jobs in Houston, TX look for? The top searched job categories for Machine Learning Engineer Intern jobs in Houston, TX are:
What cities near Houston, TX are hiring for Machine Learning Engineer Intern jobs? Cities near Houston, TX with the most Machine Learning Engineer Intern job openings:
Infographic showing various Machine Learning Engineer Intern job openings in Houston, TX as of June 2026, with employment types broken down into 76% Full Time, 23% Part Time, and 1% Temporary. Highlights an 95% Physical, 2% Hybrid, and 3% Remote job distribution, with an average salary of $40,666 per year, or $19.6 per hour.

Senior Machine Learning Engineer

Beth Page tech

Houston, TX โ€ข On-site

$99K - $137K/yr

Contractor

Posted 7 days ago


Job description

Job Title: Senior Machine Learning Engineer

Location: Houston, TX

Environment: Standard, 5-days onsite

Job Description :

ย 

Must-Have (Technical Expertise & Core Responsibilities)

  • Deep Neural Networks (DNN):
    • Hands-on experience with CNN, RNN, Graph Neural Networks, and transformers.
    • Proficiency in hyperparameter optimization, autoencoders, model evaluation, and error metrics.
  • Generative AI:
    • Strong knowledge of LLMs (BERT, GPT, etc.), embeddings, and supervised fine-tuning.
    • Experience with Reinforcement Learning, RAG (Retrieval-Augmented Generation), and Agentic AI.
    • Familiarity with GraphRAG and LLM-as-a-judge architectures.
  • Predictive Analytics:
    • Expertise in classification, regression, anomaly detection, and sequence modeling.
    • Practical application of NLP techniques (sentiment analysis, entity recognition) and knowledge graphs.

Core Responsibilities:

  • Design, train, and optimize DNN and generative models for real-world business problems.
  • Implement LLM-based solutions (fine-tuning, RAG, agents) to enhance decision-making.
  • Develop predictive models for trading, risk assessment, and operational efficiency.
  • Collaborate with teams to integrate AI/ML solutions into production systems.
  • Rigorously evaluate models using appropriate metrics and error analysis.

Qualifications & Skills:

  • Masterโ€™s/Ph.D. in Computer Science, ML, or related field.
  • 5-7+ years of industry experience in applying DNN, generative AI, and predictive analytics.
  • Python mastery (TensorFlow/PyTorch, Transformers, Scikit-learn).
  • Cloud (AWS) and containerization (Docker) experience.

Nice-to-Have (Preferred Experience):

  • Production experience with GenAI models in the energy/commodities trading sector.
  • Experience with interactive dashboards (Dash, Streamlit) and time series modeling.
  • Knowledge of data orchestrators (Airflow, Dagster) and CI/CD pipelines.