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Apprentice Machine Learning Testing Jobs in League City, TX

... testing. * Knowledge of backtesting frameworks, predictive modeling, and signal evaluation techniques. * Experience applying machine learning techniques and modern AI tools, including large language ...

Engineer

Houston, TX · On-site

$100K - $150K/yr

Experience with machine learning frameworks such as TensorFlow or PyTorch. * Familiarity with ... Conduct system testing and validation to ensure reliability and accuracy of the implemented ...

Participate in the full software development lifecycle, including planning, development, testing ... Strong understanding of machine learning algorithms, data structures, and software design patterns.

General Information

Houston, TX · On-site

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

Build in Python and, where useful, other languages to deliver machine learning systems, APIs ... Recommend and implement architecture for model and agent pipelines, CI/CD, testing, deployment ...

AI Solutions Engineering Delivery Lead

Houston, TX · On-site

$97K - $128K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... testing, validation, and operational excellence - Establish and drive consistent quality control ...

Integrate machine learning models into workflows using AI Center . * Build document extraction ... API testing, UI testing, mobile automation frameworks, and test data management. * Strong ...

Showing results 41-60

Apprentice Machine Learning Testing information

See League City, TX salary details

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How much do apprentice machine learning testing jobs pay per hour?

As of Aug 20, 2026, the average hourly pay for apprentice machine learning testing in League City, TX is $16.58, according to ZipRecruiter salary data. Most workers in this role earn between $13.99 and $18.12 per hour, depending on experience, location, and employer.

What does an apprentice machine learning testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What kinds of projects or tasks can I expect to work on as an apprentice machine learning testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

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

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in League City, TX?

For Apprentice Machine Learning Testing jobs in League City, TX, the most frequently searched job titles are:

What job categories do people searching Apprentice Machine Learning Testing jobs in League City, TX look for?

The top searched job categories for Apprentice Machine Learning Testing jobs in League City, TX are:

What cities near League City, TX are hiring for Apprentice Machine Learning Testing jobs?

Cities near League City, TX with the most Apprentice Machine Learning Testing job openings:

Analyst, Senior Data Engineering

Enterprise Products

Houston, TX

$82K - $103K/yr

Full-time

Re-posted 18 days ago


Enterprise Products rating

9.2

Company rating: 9.2 out of 10

Based on 40 frontline employees who took The Breakroom Quiz

1st of 53 rated energy and utility


Job description

Enterprise Products Partners L.P. is one of the largest publicly traded partnerships and a leading North American provider of midstream energy services to producers and consumers of natural gas, NGLs, crude oil, refined products and petrochemicals. Our services include: natural gas gathering, treating, processing, transportation and storage; NGL transportation, fractionation, storage and import and export terminals; crude oil gathering, transportation, storage and terminals; petrochemical and refined products transportation, storage and terminals; and a marine transportation business that operates primarily on the United States inland and Intracoastal Waterway systems. The partnership’s assets include approximately 50,000 miles of pipelines; 260 million barrels of storage capacity for NGLs, crude oil, refined products and petrochemicals; and 14 billion cubic feet of natural gas storage capacity.

We are currently seeking an experienced Python Software Engineer to join the Big Data and Advanced Analytics department.  The Python Software Engineer will work closely with Data Engineers and Data Scientists to solve real-world oil and gas midstream problems using advanced analytics and machine learning.

  • Work directly with subject matter experts to develop high quality, reliable, scalable, software products.
  • Design and implement frameworks and tools to streamline the machine learning process.
  • Implement data manipulation and transformation logic to support various use cases.
  • Leverage software architecture and design patterns to develop fault tolerant microservices.
  • Document code and architectural decisions to support maintainability.
  • Implement processes to ensure coding standards, code quality, documentation, and test coverage.

The successful candidate will meet the following qualifications:

  • 5 years of programming experience in Python.
  • Expertise in developing and maintaining data pipelines.
  • Experience in software engineering practices such as Design Principles and Patterns, Unit Testing, Refactoring, CI/CD, and version control.
  • Expertise in Object-Oriented Design Principals and Functional Programming Principals.
  • Experience with common Python Data Engineering packages including Pandas, Numpy, Pyarrow, Pytest, Scikit-Learn, and Boto3.
  • Experience in implementing distributed computing systems.
  • Knowledgeable of DevOps Principles.
  • Experience in designing modular, reusable software components. 
  • Experience in developing API endpoints and microservices..

What Enterprise Products employees say

Pay

Benefits

Hours and flexibility

Workplace

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