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Apprentice Machine Learning Testing Jobs in Los Angeles, CA

Paramount

Lead Machine Learning Operations Engineer

Burbank, CA · On-site

$109K - $143K/yr

Lead Machine Learning Operations Engineer Personalization & Recommendation Systems Overview We're ... Experience with A/B testing, experiment guardrails, counterfactual evaluation, or offline-to-online ...

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 ...

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

As of Jul 16, 2026, the average hourly pay for apprentice machine learning testing in Los Angeles, CA is $20.86, according to ZipRecruiter salary data. Most workers in this role earn between $17.60 and $22.79 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 Los Angeles, CA? For Apprentice Machine Learning Testing jobs in Los Angeles, CA, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Los Angeles, CA look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Apprentice Machine Learning Testing jobs? Cities near Los Angeles, CA with the most Apprentice Machine Learning Testing job openings:
Apprentice Machine Learning Testing jobs near you

Senior Machine Learning Engineer - Disney Streaming

Disney Entertainment and ESPN Product & Technology

Glendale, CA

$110K - $152K/yr

Full-time

Posted 15 days ago

Job description

Role Location: 

This is an on-site role requiring 4 days in-person at designated office location.

Disney Entertainment and ESPN Product & Technology

Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.

The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world. 


Here are a few reasons why we think you’d love working here:

Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.

Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally. 

Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.

Product Engineering is a unified team responsible for the engineering of Disney Entertainment & ESPN digital and streaming products and platforms. This includes product engineering, media engineering, quality assurance, engineering behind personalization, commerce, lifecycle, and identity.

Job Summary:

Our team designs and builds models that directly shape the user experience – powering personalization and engagement across our Disney Streaming’s suite of streaming video apps, notably Disney+ and Hulu. With a strong product mindset and a focus on usability, we ensure every ML-driven product enhances how users discover, interact, and enjoy our experiences.

As a member of this team you will collaborate across Engineering, Product, and Data teams to apply machine learning methods to meet strategic product personalization goals, explore innovative, cutting edge techniques that can be applied to recommendations, and constantly seek ways to optimize operational processes.

This is an Individual Contributor role. You will be expected to lead recommendation and personalization algorithm research, development, and productionization for product areas, and to coordinate requirements and manage stakeholder expectations with Product, Engineering, and Editorial teams. As an IC, you will also be responsible for helping to set the roadmap for algorithmic work — not only for how to approach product requests for new recommendation features, but for helping to drive larger company objectives in the areas of personalization and recommendations.

Responsibilities and Duties of the Role:

  • Algorithm Development and Maintenance: Utilize cutting edge machine learning methods to develop algorithms for personalization, recommendation, and other predictive systems; maintain algorithms deployed to production and be the point person in explaining methodologies to technical and non-technical teams

  • Feature Engineering and Optimization: Develop and maintain ETL pipelines using orchestration tools such as Airflow and Jenkins; deploy scalable streaming and batch data pipelines to support petabyte scale datasets

  • Development Best Practices: Maintain existing and establish new algorithm development, testing, and deployment standards

  • Collaborate with product and business stakeholders: Identify and define new personalization opportunities and work with other data teams to improve how we do data collection, experimentation and analysis

Required Education, Experience/Skills/Training:

Basic Qualifications

  • 5+ years of experience developing machine learning models, performing large-scale data analysis, and/or data engineering experience

  • 5+ years writing production-level, scalable code (Python, SQL)

  • 3+ years of experience developing algorithms for deployment to production systems

  • In-depth understanding of modern machine learning (e.g. deep learning methods), models, and their mathematical underpinnings

  • Experience deploying and maintaining pipelines and in engineering big-data solutions using technologies like Databricks, S3, and Spark

  • Ability to gauge the complexity of machine learning problems and a willingness to execute simple approaches for quick, effective solutions as appropriate

  • Strong written and verbal communication skills

Preferred Qualifications

  • MS or PhD in statistics, math, computer science, or related quantitative field

  • Production experience with developing content recommendation algorithms at scale

  • Experience building and deploying full stack ML pipelines: data extraction, data mining, model training, feature development, testing, and deployment

  • Familiar with metadata management, data lineage, and principles of data governance

  • Experience loading and querying cloud-hosted databases

Experience with:

  • AWS, Databricks

Required Education  

  • Bachelor’s Degree in Computer Science, Math, Statistics, or related quantitative field
    #disneytech


The hiring range for this position in New York, NY is $148,700 - $199,400 per year and in Santa Monica, CA is $141,900 - $190,300. The base pay actually offered will take into account internal equity and also may vary depending on the candidate’s geographic region, job-related knowledge, skills, and experience among other factors. A bonus and/or long-term incentive units may be provided as part of the compensation package, in addition to the full range of medical, financial, and/or other benefits, dependent on the level and position offered.

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