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Machine Learning Engineer Jobs in Riverside, CA (NOW HIRING)

Yum! Brands

Associate Manager Machine Learning

Irvine, CA · Hybrid

$134K - $158K/yr

We are hiring a Manager, Machine Learning (MLE) to lead the development and operationalization of ... You will manage a team of MLEs and partner with AI Engineers, QA, and DevOps to deliver high ...

PDS Health

Sr Engineer, AI Solutions

Irvine, CA · On-site

$130K - $168K/yr

The Senior Engineer, AI Solutions collaborates with cross-functional teams to design, develop, and ... Design and implement AI/Machine Learning (ML) solutions across domains such as computer vision and ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results ...

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site +1

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

FieldAI

Senior Software Engineer, MLOps

Irvine, CA · On-site

$131K - $173K/yr

You will work closely with machine learning engineers, robotics engineers, and infrastructure teams to ensure reliable training, evaluation, deployment, and monitoring of ML models. This is an ...

Turion Space

Lead AI Engineer

Irvine, CA

$110K - $144K/yr

Description The Lead AI Engineer will be responsible for defining and driving the AI strategy ... Design, develop, and deploy advanced AI models and algorithms, including machine learning, deep ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Riverside, CA

Machine Learning Engineer information

See Riverside, CA salary details

$32.9K

$134.3K

$201.9K

How much do machine learning engineer jobs pay per year?

As of Jun 26, 2026, the average yearly pay for machine learning engineer in Riverside, CA is $134,341.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,900.00 and $161,700.00 per year, depending on experience, location, and employer.

Is ML full of coding?

Machine Learning Engineers typically do a significant amount of coding, especially in languages like Python or R, to develop algorithms, preprocess data, and build models. Strong programming skills are essential, along with knowledge of frameworks such as TensorFlow or PyTorch, but the role also involves data analysis, model evaluation, and collaboration with teams. Coding is a core component of the job, though some tasks may involve model deployment and optimization that require different skills.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or technology can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as they develop, implement, and maintain AI systems, requiring specialized skills in programming, data analysis, and model optimization. Roles that involve complex problem-solving, creativity, and human interaction—such as healthcare professionals, educators, skilled tradespeople, and certain managerial positions—are also expected to persist despite AI advancements. These jobs typically require emotional intelligence, adaptability, and domain expertise that AI cannot easily replicate.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What is the difference between Machine Learning Engineer vs Data Scientist?

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in Riverside, CA? The most popular types of Machine Learning Engineer jobs in Riverside, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Riverside, CA? For Machine Learning Engineer jobs in Riverside, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Riverside, CA look for? The top searched job categories for Machine Learning Engineer jobs in Riverside, CA are:
What cities near Riverside, CA are hiring for Machine Learning Engineer jobs? Cities near Riverside, CA with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Riverside, CA as of June 2026, with employment types broken down into 1% As Needed, 90% Full Time, 5% Part Time, 2% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,341 per year, or $64.6 per hour.
Associate Manager Machine Learning

Associate Manager Machine Learning

Yum! Brands

Irvine, CA • Hybrid

$134K - $158K/yr

Other

Posted 10 days ago

Yum! Brands rating

3.9

Company rating: 3.9 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

Job description

We are hiring a Manager, Machine Learning (MLE) to lead the development and operationalization of machine learning systems powering the Taco Bell Voice AI experience. This role is central to ensuring performance, scalability, and reliability across real-time models that support speech, natural language understanding, and agent behavior.

You will manage a team of MLEs and partner with AI Engineers, QA, and DevOps to deliver high-quality agent performance with a strong focus on latency, integration with restaurant systems (e.g., HME, POS), and production excellence.

Key Responsibilities:

  • ML System Design & Architecture:
    • Lead the design of end-to-end ML pipelines for speech, ASR, and NLU modules.
    • Optimize model performance for real-time interaction, including latency, uptime, and inference cost.
    • Implement and evolve model evaluation, testing, and monitoring frameworks.
  • Infrastructure & Integration:
    • Collaborate with engineering to integrate ML components with external systems (HME, menu boards, POS).
    • Support scalable deployment strategies across markets and environments.
    • Drive MLOps best practices in CI/CD, rollback, logging, and observability.
  • Leadership & Collaboration:
    • Mentor and guide a team of MLEs and junior ML engineers.
    • Partner with product, AI engineering, and QA to define technical scope, delivery targets, and quality standards.
    • Support internal upskilling and technical review of AI-driven components.

Required Qualifications:

  • 6+ years of experience in machine learning, including at least 2 years in technical leadership roles.
  • Proven expertise in deploying NLP, ASR, or LLM-based systems in real-time applications.
  • Strong programming skills in Python and ML tooling (e.g., PyTorch, HuggingFace, ONNX, MLflow).
  • Experience optimizing model latency and integrating ML with backend infrastructure.

Preferred Qualifications:

  • Experience in QSR, retail, or voice-driven customer service environments.
  • Background in integrating AI with physical systems (HME, POS, IoT).
  • Familiarity with LoRA, quantization, distillation, and model compression techniques.

Location & Travel:

  • This role is based in Irvine, CA at the Taco Bell offices.
  • Hybrid work model: in-office 1-2 days per week required.
  • Occasional travel to deployment sites or test locations may be needed.

Salary Range: $134,500 to $158,300 annually + bonus eligibility. This is the expected salary range for this position. Ultimately, in determining pay, we'll consider the successful candidate's location, experience, and other job-related factors.

Yum! Brands, Inc., based in Louisville, Kentucky, and its subsidiaries franchise or operate a system of over 59,000 restaurants in more than 155 countries and territories under the company's concepts - KFC, Taco Bell, Pizza Hut and Habit Burger & Grill. The Company's KFC, Taco Bell and Pizza Hut brands are global leaders of the chicken, Mexican-style food, and pizza categories, respectively. Habit Burger & Grill is a fast casual restaurant concept specializing in made-to-order chargrilled burgers, sandwiches and more. In 2024, Yum! was named to the Dow Jones Sustainability Index North America, and the company was recognized among TIME Magazine's list of Best Companies for Future Leaders, Newsweek's list of America's Most Responsible Companies and USA Today's America's Climate Leaders. Yum! also received widespread recognition in 2023, including being listed on the Bloomberg Gender-Equality Index; and Forbes' list of America's Best Employers for Diversity. In addition, KFC, Taco Bell and Pizza Hut brands were ranked in the top five of Entrepreneur's Top Global Franchises Ranking for 2023.

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