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Machine Learning Engineer Intern Jobs in Fullerton, CA

They are seeking a 3D Machine Learning Engineer to design, implement, and maintain advanced 3D machine learning models for processing reality capture data, contributing to automated progress tracking ...

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Machine Learning Engineer Intern information

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$26.6K

$44.4K

$91.8K

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

As of Sep 7, 2026, the average yearly pay for machine learning engineer intern in Fullerton, CA is $44,427.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,900.00 and $48,000.00 per year, depending on experience, location, and employer.

What is a machine learning engineer intern?

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 do machine learning engineer interns do?

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 skills and qualifications are needed to thrive as a machine learning engineer intern?

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 Fullerton, CA?

The most popular types of Machine Learning Engineer jobs in Fullerton, CA are:

What job categories do people searching Machine Learning Engineer Intern jobs in Fullerton, CA look for?

The top searched job categories for Machine Learning Engineer Intern jobs in Fullerton, CA are:

What cities near Fullerton, CA are hiring for Machine Learning Engineer Intern jobs?

Cities near Fullerton, CA with the most Machine Learning Engineer Intern job openings:

Infographic showing various Machine Learning Engineer Intern job openings in Fullerton, CA as of August 2026, with employment types broken down into 1% As Needed, 68% Full Time, 27% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $44,427 per year, or $21.4 per hour.

Principal Machine Learning Engineer

5014 Disney Entertainment & Sports LLC

Glendale, CA โ€ข On-site

$207 - $278/hr

Other

Posted 12 days ago


Job description

Job Posting Title: Principal Machine Learning Engineer Req ID: 10157433

Job Description:

Disney Entertainment and ESPN Product & Technology Technology is at the heart of Disneyโ€™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 โ€“ all working to build and advance the technological backbone for Disneyโ€™s media business globally. The team marries technology with creativity to build worldโ€‘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 Companyโ€™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 youโ€™d love working here:
  • Building the future of Disneyโ€™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, Disneyโ€™s technology and products serve as a signature doorway for fans' connections with the companyโ€™s brands and stories. Disney+. Hulu. ESPN. ABC. ABC Newsโ€ฆand many more. These products and brands โ€“ and the unmatched stories, storytellers, and events they carry โ€“ 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.
Job Summary:

As a Principal Machine Learning Engineer, you will define and own the technical architecture and strategic direction of the N&E ML Platform across a large, complex problem space spanning Disney's News & Entertainment portfolio. You will drive stepโ€‘function improvements in personalization, recommendation systems, and ML infrastructure - not just at the feature level, but across entire product and platform domains. You will serve as a thought leader who bridges business objectives and technical execution, partnering with senior leadership, product, and crossโ€‘org engineering communities to set the standard for ML excellence within News & Entertainment. Your impact will be measured by the quantifiable outcomes you drive for our guests and the durable technical foundations you build for the teams around you.

Responsibilities and Duties of the Role:
  • Focus on major areas of work, typically 20% or more of role
  • Architecture Ownership: Define and own the endโ€‘toโ€‘end architecture of the N&E ML platform across a large problem space spanning ABC News, ABC Entertainment, National Geographic, Marvel, and Disney Studios. Author architecture documents, drive them through review, and oversee implementation to ensure solutions are scalable, reliable, and aligned with platformโ€‘wide standards.
  • Strategic Technical Leadership: Identify, scope, and prioritize the most impactful and timeโ€‘sensitive ML workstreams across the N&E portfolio. Break down and sequence complex initiatives, proactively surface risks to leadership, and drive outcomes with a clear metricsโ€‘driven mindset.
  • ML Platform & Infrastructure: Drive the design and evolution of infrastructure supporting the full ML lifecycle across diverse content types and brands: data pipelines, workflow orchestration, feature stores, batch training, and lowโ€‘latency online serving. Champion reliability, quality, and operational excellence across the platform.
  • Innovation & Industry Awareness: Stay at the forefront of industry trends in ML, AI, and data engineering. Proactively identify and champion the adoption of new technologies, frameworks, and patterns that drive improvement across the N&E portfolio (e.g. recommendation systems, LLMs, RAGs, object detection, autogenerated content tagging).
  • Incident & Reliability Ownership: Own and speak to production incidents during weekly meetings with leadership. Hold the team to the right engineering processes and drive a culture of reliability, observability, and continuous improvement across the N&E ML problem space.
  • Crossโ€‘Org Engagement: Actively participate in and contribute to the broader Machine Learning community across Disney Entertainment & ESPN. Drive and influence engineering standards, crossโ€‘org programs, and best practices that extend beyond the N&E ML team.
  • Business & Objectives Alignment: Serve as a thought leader who deeply understands the business objectives and problems across the N&E portfolio - not just the technical ones. Lead metricsโ€‘driven programs that connect ML platform investments directly to measurable guest experience and business outcomes across all brands.
  • Mentorship & Culture: Mentor and elevate senior engineers, fostering a culture of ownership, technical rigor, and continuous learning. Be a confident, vocal, and optimistic leader who inspires the team and drives outcomes people want to rally around.
Required Education, Experience/Skills/Training:

Basic Qualifications

Bachelorโ€™s degree in computer science, Information Systems, Statistics, Math, or comparable field of study, and/or equivalent work experience

10+ years of experience building and operating ML engineering systems in production environments, with a track record of owning large, complex problem spaces

Deep expertise in data science, deep learning algorithms, and statistical methods applied to realโ€‘world, largeโ€‘scale engineering problems

Demonstrated experience owning architecture across a significant platform or product domain - including authoring architecture documents, driving reviews, and leading implementation

Proven ability to drive quantifiable improvements in ML platform capabilities, personalization quality, or recommendation system performance

Experience designing and evolving backend microservices for largeโ€‘scale distributed systems using REST

Strong expertise with cloud infrastructure, preferably AWS (Step Functions, Lambda, Glue, SQS, SNS, Personalize)

Deep handsโ€‘on experience with big data technologies such as Databricks, Spark, Kinesis, and Kafka

Experience leading incident response for high priority incidents and driving reliability programs across a team or platform

Active participation in crossโ€‘organizational engineering communities, standardsโ€‘setting, and architectural governance

Proven track record as a metricsโ€‘driven technical leader who connects engineering decisions to business outcomes

Exceptional communication, influence, and collaboration skills โ€” comfortable presenting to and aligning senior leadership and crossโ€‘functional stakeholders

Experience working in Agile/Scrum environments with strong prioritization and stakeholder management skills

Preferred Qualifications:
  • Experience with agentic AI workflows and frameworks (e.g. LangGraph, AutoGen, CrewAI) and applying them to automate complex ML and data engineering tasks
  • Familiarity with AIโ€‘assisted development tools such as Claude, Cursor, or GitHub Copilot to accelerate software development lifecycle and engineering productivity
  • Familiarity with prompt engineering, fineโ€‘tuning, and evaluation frameworks for large language models in production environments
  • Experience with MLOps platforms and modern model lifecycle management tools (e.g. MLflow, SageMaker, Vertex AI)

The hiring range for this position in Glendale, California is $207,400 - $278,100 per year. The base pay actually offered will take into account internal equity and also may vary depending on the candidateโ€™s geographic region, jobโ€‘related knowledge, skills, and experience among other factors. A bonus and/or longโ€‘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.

Job Posting Segment:

Product Engineering

Primary Business: PE - Streaming Backend

Primary Job Posting Category: Machine Learning

Employment Type: Full time

Primary City, State, Region, Postal Code: Glendale, CA, USA

Alternate City, State, Region, Postal Code: USA - NY - 7 Hudson Square

Date Posted: 2026-08-21

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