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

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Machine Learning Engineer II

Irvine, CA · On-site

$104K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

Senior Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

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 ...

Senior Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

You'll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond ...

You'll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond ...

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

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Showing results 1-20

Machine Learning Engineer information

See Irvine, CA salary details

$33.8K

$138.2K

$207.7K

How much do machine learning engineer jobs pay per year?

As of Jul 5, 2026, the average yearly pay for machine learning engineer in Irvine, CA is $138,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $108,900.00 and $166,400.00 per year, depending on experience, location, and employer.

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-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants 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 AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

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 engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Irvine, CA? The most popular types of Machine Learning Engineer jobs in Irvine, CA are:
What are popular job titles related to Machine Learning Engineer jobs in Irvine, CA? For Machine Learning Engineer jobs in Irvine, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Irvine, CA look for? The top searched job categories for Machine Learning Engineer jobs in Irvine, CA are:
What cities near Irvine, CA are hiring for Machine Learning Engineer jobs? Cities near Irvine, CA with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Irvine, CA as of June 2026, with employment types broken down into 1% As Needed, 97% Full Time, 1% Temporary, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $138,220 per year, or $66.5 per hour.
Sr Machine Learning Engineer

Sr Machine Learning Engineer

Yum Brands

Irvine, CA

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 26 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 seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data Scientists, Data Engineers, and Analytics stakeholders to deploy, maintain, and improve production ML workflows across AWS. The ideal candidate combines strong software engineering and MLOps fundamentals with a passion for building reliable, scalable machine learning systems.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. 
  • 3+ years of experience in Machine Learning Engineering, MLOps, Software Engineering, or related technical roles. 
  • Strong Python development skills, including experience with pandas, PyTorch, scikit-learn, boto3, and SQL. 
  • Experience working with AWS services such as SageMaker, Step Functions, Lambda, S3, IAM, and ECR. 
  • Experience developing or supporting orchestration workflows using Airflow, Glue, or similar technologies. 
  • Familiarity with cloud-based data platforms such as Snowflake, Redshift, or Athena. 
  • Experience with Docker, CI/CD pipelines, source control workflows, and software development best practices. 
  • Strong troubleshooting and debugging skills across distributed systems and machine learning workflows. 
  • Ability to collaborate effectively with technical and non-technical stakeholders. 

Preferred Qualifications

  • Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. 
  • Familiarity with MLflow, Hydra/OmegaConf, FastAPI, or similar ML platform tooling. 
  • Experience supporting deep learning workflows in production environments. 
  • Exposure to infrastructure-as-code tools such as Terraform, Terragrunt, or CloudFormation. 
  • Experience working with customer analytics, marketing measurement, or recommendation systems. 

Salary Range: 129,800 - 162,200 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.

Benefits: Employees (and their eligible family members) may enroll in the following types of insurance coverage: medical, dental, vision, legal, and accidental death and dismemberment, as well as FSA/HSA (depending on enrolled medical plan). Yum! also provides short-term disability, long-term disability, and life insurance. Employees may enroll in our 401(k) plan. Yum! provides 4 weeks of vacation, paid sick leave, 10 paid holidays, a floating day off and 2 paid days for volunteer time each calendar year. To learn more about working at Yum! -Click here. 

At Yum!, one of our core values is to Believe in ALL People. This means seeing the value in everyone and unlocking their full potential to be their best self. YUM! Brands, Inc. (including its subsidiaries Yum Restaurant Services Group, LLC ("YRSG") and Yum Connect, LLC ("Yum Digital and Technology")(collectively, "Yum") is proud to be an equal opportunity employer and is committed to equity, inclusion, and belonging for all dimensions of diversity.  We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, veteran status, disability status, age, or any other protected characteristic. Yum! is committed to working with and providing reasonable accommodation to applicants with disabilities or special needs.

US Job Seekers/Employees - Click here to view the "Know Your Rights" poster and supplement and the Pay Transparency Policy Statement.

Required Qualifications

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. 
  • 3+ years of experience in Machine Learning Engineering, MLOps, Software Engineering, or related technical roles. 
  • Strong Python development skills, including experience with pandas, PyTorch, scikit-learn, boto3, and SQL. 
  • Experience working with AWS services such as SageMaker, Step Functions, Lambda, S3, IAM, and ECR. 
  • Experience developing or supporting orchestration workflows using Airflow, Glue, or similar technologies. 
  • Familiarity with cloud-based data platforms such as Snowflake, Redshift, or Athena. 
  • Experience with Docker, CI/CD pipelines, source control workflows, and software development best practices. 
  • Strong troubleshooting and debugging skills across distributed systems and machine learning workflows. 
  • Ability to collaborate effectively with technical and non-technical stakeholders. 

Preferred Qualifications

  • Experience with Bayesian or probabilistic modeling frameworks such as PyMC or ArviZ. 
  • Familiarity with MLflow, Hydra/OmegaConf, FastAPI, or similar ML platform tooling. 
  • Experience supporting deep learning workflows in production environments. 
  • Exposure to infrastructure-as-code tools such as Terraform, Terragrunt, or CloudFormation. 
  • Experience working with customer analytics, marketing measurement, or recommendation systems. 
  • Support the deployment, monitoring, and ongoing maintenance of media measurement and customer modeling systems in partnership with Data Science and Engineering teams. 
  • Develop and maintain SageMaker processing and training jobs, model endpoints, and supporting infrastructure across development, testing, and production environments. 
  • Contribute to Step Functions, Lambda functions, and Airflow (MWAA) workflows that orchestrate model training, scoring, retraining, and analytics pipelines. 
  • Support MLflow model registration and promotion processes, configuration management, and versioned model artifacts. 
  • Build and maintain Docker images, ECR repositories, and GitLab CI/CD pipelines to enable reliable model deployment and release processes. 
  • Help productionize machine learning models and data pipelines that support customer analytics, scoring, and decisioning use cases. 
  • Investigate and resolve production issues using CloudWatch, DataDog, SageMaker logs, and workflow monitoring tools. 
  • Collaborate with cross-functional partners to implement platform enhancements, improve operational reliability, and deliver new capabilities. 
  • Contribute to engineering best practices, documentation, testing strategies, and operational procedures. 

What Yum! Brands employees say

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