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Apprentice Machine Learning Testing Jobs in Oceanside, CA

Apple Inc.

Machine Learning Engineer- Gen AI

San Diego, CA · On-site

$142.30 - $214.30/hr

Master's in Artificial intelligence, Machine Learning, Computer Science, Statistics, Operations ... Experience applying ML techniques in manufacturing, testing, or hardware optimization is a major ...

FICO

Lead Machine Learning Engineer

San Diego, CA · On-site

$122K - $192K/yr

... machine learning; experience working with cloud-based and distributed architectures, large real ... Experience with testing frameworks, A/B testing, performance optimization, and production ...

Petco

Sr. Engineer, AI Platform Engineering

San Diego, CA · On-site

$107K - $147K/yr

Design and develop end-to-end machine learning pipelines, emphasizing scalability, reliability, and performance. * Implement MLOps best practices for dynamic model training, testing, deploying and ...

Qualcomm

Software Engineer, Core AI Software

San Diego, CA · On-site

$122.80 - $184.20/hr

Validate, analyze, and optimize the performance and accuracy of software through detailed testing of machine learning use cases. * Debug complex issues, perform root cause analysis, and ensure high ...

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All JobsApprentice Machine Learning Testing JobsApprentice Machine Learning Testing Jobs in Oceanside, CA

Apprentice Machine Learning Testing information

See Oceanside, CA salary details

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

As of Aug 21, 2026, the average hourly pay for apprentice machine learning testing in Oceanside, CA is $20.03, according to ZipRecruiter salary data. Most workers in this role earn between $16.92 and $21.88 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.

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Apprentice Machine Learning Testing jobs near you

Data Scientist / Machine Learning Engineer

Trabus Technologies

San Diego, CA • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 9 days ago

Job description

Data Scientist / Machine Learning Engineer
About TRABUS Technologies
TRABUS Technologies (TRABUS) is a minority-owned, Service-Disabled Veteran-Owned Small Business (SDVOSB) headquartered in San Diego, California. Since 2010, TRABUS has provided advanced wireless technology solutions, cybersecurity expertise, artificial intelligence capabilities, and engineering support to federal and commercial clients.
Recognized on the Inc. 5000 list for seven consecutive years, TRABUS is a dynamic, forward-leaning organization committed to solving complex, real-world challenges and delivering mission-ready solutions that meet and exceed customer expectations.
Position Overview
TRABUS Technologies is seeking a highly motivated Data Scientist / Machine Learning Engineer to join our growing Artificial Intelligence and Data Science team.
In this role, you will combine machine learning, data science, and software engineering skills to support a variety of AI-based projects, including resource planning for ship maintenance, marine transportation, and climate and environmental informatics.
The successful candidate will develop machine learning models that provide predictive insights and analytics for robust, web-based, full-stack AI applications supporting both government customers - including the Department of Defense (DoD), Department of Transportation (DoT), and National Oceanic and Atmospheric Administration (NOAA) - and commercial customers.
Key Responsibilities
  • Develop code to extract, clean, transform, and preprocess training datasets from disparate data formats, sources, and APIs.
  • Research, evaluate, select, and develop appropriate Machine Learning (ML) and Deep Learning (DL) algorithms and models.
  • Apply AI/ML techniques across diverse data domains, including Navy, transportation, environmental sciences, healthcare, and public safety.
  • Collaborate with the TRABUS Data Science team to develop scalable AI solutions incorporating technologies such as:
    • Large Language Models (LLMs)
    • Retrieval-Augmented Generation (RAG)
    • Prompt Engineering
    • Computer Vision
    • Natural Language Processing (NLP)
  • Work alongside AI/ML and DevOps engineers to develop automated AI workflows that continuously generate predictions and inferences.
  • Develop validation and testing routines to measure model performance and evaluate the quality and accuracy of predictions.
  • Analyze large datasets and data streams to identify patterns, trends, and actionable insights.
  • Support the integration of machine learning models into web-based and full-stack AI applications.
  • Collaborate with technical teams throughout the development, testing, integration, and deployment lifecycle.

Required Qualifications
  • Minimum of 2 years of programming experience using Python.
  • Completed coursework in Machine Learning, Deep Learning, Algorithm Design, and Data Science.
  • Knowledge and experience with Python data science and machine learning libraries such as:
    • Pandas
    • scikit-learn
    • Keras
    • TensorFlow
    • PyTorch
  • Strong Python programming skills with the ability to process and analyze large datasets and data streams.
  • Understanding of databases, data structures, and API-based ETL operations.
  • Strong working knowledge of Linux or Unix-based operating systems.
  • Familiarity with Python web frameworks such as FastAPI, Django, and Flask.
  • Experience working with Git repositories and version control.
  • Ability to work collaboratively within multidisciplinary technical teams.
  • U.S. Citizenship is required.
  • Must be able to obtain and maintain a final DoD-adjudicated Secret security clearance.

Desired Qualifications
  • Current DoD-adjudicated Secret security clearance.
  • Strong knowledge of DevOps tools, processes, and best practices.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Familiarity with Agile software development methodologies.
  • Experience working within Agile development environments.
  • Experience with Continuous Integration/Continuous Deployment (CI/CD) pipelines.
  • Proficiency with Microsoft Office applications.
  • Strong written and verbal communication skills.
  • Strong attention to detail and commitment to procedural compliance.
  • Ability to manage multiple responsibilities and priorities while meeting established deadlines.

Education
  • Bachelor's degree in Computer Science, Computer Engineering, Data Science, or another related STEM discipline.
  • Master's degree preferred.

Benefits
TRABUS Technologies offers a competitive compensation package and comprehensive employee benefits, including:
  • Paid Time Off (PTO)
  • Paid Holidays
  • Health Insurance
  • Dental Insurance
  • Vision Insurance
  • Flexible Spending Account (FSA)
  • 401(k)
  • Life and AD&D Insurance

Equal Employment Opportunity
TRABUS Technologies is an Equal Employment Opportunity Employer. We are committed to the principles of equal employment opportunity and will not discriminate against any employee or applicant for employment because of race, color, religion, sex, national origin, age, disability, veteran status, or any other status protected by applicable federal, state, or local discrimination laws.

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