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Apprentice Machine Learning Testing Jobs in Compton, CA

RBC Bearings

Machinist Apprentice

Santa Ana, CA · On-site

$22/hr

Machinist Apprentice - Santa Ana, CA DESCRIPTION: The Machinist Apprentice will assist experienced ... This role involves learning machining processes, interpreting technical drawings, and ensuring ...

CIM Group

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$140K - $179K/yr

They are seeking a Senior Machine Learning Ops Engineer to lead the design and maintenance of ... testing, validation, and deployment using Databricks Workflows and Asset Bundles. • Set up robust ...

Apple

User Acceptance Testing Specialist

Culver City, CA · On-site

The candidate will blend thetraditional validation practices with machine learning evaluation, test ... Experience working on End to End testing across mobile applications and developing test plan, test ...

CIM Group

Sr. Machine Learning Ops Engineer

Los Angeles, CA · On-site

$112K - $154K/yr

... testing, validation, and deployment using Databricks Workflows and Asset Bundles • Set up robust CI/CD pipelines for both traditional ML models and GenAI applications, leveraging GitHub Actions ...

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Apprentice Machine Learning Testing information

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$11

$19

$28

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

As of Jun 23, 2026, the average hourly pay for apprentice machine learning testing in Compton, CA is $19.66, according to ZipRecruiter salary data. Most workers in this role earn between $16.59 and $21.49 per hour, depending on experience, location, and employer.

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 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 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 Compton, CA? For Apprentice Machine Learning Testing jobs in Compton, CA, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Compton, CA look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Compton, CA are:
What cities near Compton, CA are hiring for Apprentice Machine Learning Testing jobs? Cities near Compton, CA with the most Apprentice Machine Learning Testing job openings:
Apprentice Machine Learning Testing jobs near you
Machine Learning (ML) Ops Engineer - IS Clinical Research - Full Time 8 Hour Days (Exempt) (Non-U...

Machine Learning (ML) Ops Engineer - IS Clinical Research - Full Time 8 Hour Days (Exempt) (Non-U...

University of Southern California

Los Angeles, CA • On-site

$145K - $240K/yr

Full-time

Posted 15 days ago

University Of Southern California rating

8.3

Company rating: 8.3 out of 10

Based on 50 frontline employees who took The Breakroom Quiz

97th of 539 rated colleges and universities

Job description

Under the direction of Information Services Leadership, the incumbent will be responsible for the full lifecycle management of machine learning models, including design, build, and maintenance of machine learning models. The MLOps Engineer will play an integral role in implementing artificial intelligence solutions across Keck Medicine of USC. The incumbent will partner with data scientists, data team members, and clinical operations to deploy, monitor, and maintain machine learning solutions that will improve patient care, support operational excellence, and advance clinical research. The incumbent will ensure seamless integration, automation, and scaling of AI solutions within the existing infrastructure by leveraging DevOps expertise. They will maintain and continuously improve MLOps pipelines for monitoring, versioning, and deploying models in production environments. The incumbent will be responsible for the end-to-end lifecycle management of artificial intelligence solutions and comes with DevOps experience, ensuring seamless integration, deployment, and automation of systems. The MLOps Engineer will implement best practices for testing, debugging, and performance monitoring of AI systems to ensure reliability and scalability.
Essential Duties:
  • Design, build and maintain production-grade machine learning models, with real-time inference, scalability, and reliability.
  • Develop end-to-end scalable ML infrastructure using cloud platforms, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure.
  • Develop AI pipelines for various data processing needs, including data ingestion, pre-processing, and search and retrieval, ensuring solutions meet all technical and business requirements.
  • Monitor model performance for data drift and concept drift detection, automate retraining processes where necessary to maintain model accuracy and relevance.
  • Collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
  • Implement and optimize CI/CD pipelines for machine learning models, automating testing and deployment processes.
  • Configure and manage monitoring and logging solutions to track model performance, system health, and anomalies, enabling timely intervention and proactive maintenance.
  • Implement version control systems for machine learning models, parameters, results and associated code to track changes and facilitate collaboration.
  • Ensure all machine learning systems meet security and compliance standards, including data protection and privacy regulations.
  • Lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.
  • Maintain clear and comprehensive documentation of MLOps processes and configuration.
  • Strong communication and collaboration skills, to collaborate cross-functionally and align on deployment strategies and technical requirements
  • Other duties as assigned.

Required Qualifications:
  • Req Bachelor's Degree Degree in computer science, engineering or closely related field
  • Req Proven experience with: Artificial intelligence and machine learning platforms (e.g., AWS, Azure or GCP). Containerization technologies (e.g., Docker) or container orchestration platforms (e.g., Kubernetes). CI/CD tools (e.g., Github Actions). Programming languages and frameworks (e.g., Python, R, SQL). MLOps engineering principles, agile methodologies, and DevOps lifecycle management. Technical writing and documentation for AI/ML models and processes. Healthcare data and machine learning use cases.
  • Req Ability to solve complex problems through troubleshooting
  • Req Deep understanding of coding, architecture, and deployment processes
  • Req Strong analytical skills with the ability to collect, organize, analyze, and disseminate significant amounts of information with attention to detail and accuracy
  • Req Excellent organizational skills and attention to detail
  • Req Self-starter with the ability to solution when requirements are vague or ambiguous

Preferred Qualifications:
  • Pref Master's degree Degree in computer science, engineering or closely related field

Required Licenses/Certifications:
  • Req Fire Life Safety Training (LA City) If no card upon hire, one must be obtained within 30 days of hire and maintained by renewal before expiration date. (Required within LA City only)

The annual base salary range for this position is $145,600.00 - $240,240.00. When extending an offer of employment, the University of Southern California considers factors such as (but not limited to) the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, federal, state, and local laws, contractual stipulations, grant funding, as well as external market and organizational considerations.
USC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, or any other characteristic protected by law or USC policy. USC observes affirmative action obligations consistent with state and federal law. USC will consider for employment all qualified applicants with criminal records in a manner consistent with applicable laws and regulations, including the Los Angeles County Fair Chance Ordinance for employers and the Fair Chance Initiative for Hiring Ordinance, and with due consideration for patient and student safety. Please refer to the Background Screening Policy Appendix D for specific employment screen implications for the position for which you are applying.
We provide reasonable accommodations to applicants and employees with disabilities. Applicants with questions about access or requiring a reasonable accommodation for any part of the application or hiring process should contact USC Human Resources by phone at (213) 821-8100, or by email at uschr@usc.edu. Inquiries will be treated as confidential to the extent permitted by law.
  • Notice of Non-discrimination
  • Employment Equity
  • Read USC's Clery Act Annual Security Report
  • USC is a smoke-free environment
  • Digital Accessibility

If you are a current USC employee, please apply to this USC job posting in Workday by copying and pasting this link into your browser:
https://wd5.myworkday.com/usc/d/inst/1$9925/9925$126972.htmld

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About University of Southern California

Sourced by ZipRecruiter

The University of Southern California (USC) is not a conventional company, but a private research university established in the heart of Los Angeles, CA, US. Founded in 1880, it's one of the oldest private research universities in California. USC operates in the education industry providing primary services of higher education, research, and community development. This prestigious institution offers a comprehensive array of undergraduate, graduate, and professional programs across various disciplines, including the humanities, social sciences, and STEM (Science, Technology, Engineering, and Mathematics). The University is guided by its commitment to foster creativity, innovation, leadership, and discovery through academic excellence.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Los Angeles , CA, US

Year founded

1880

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