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Junior Machine Learning Engineer Jobs in Irvine, CA

Yum Brands

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 ...

Yum! Brands

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 ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120 - $185/hr

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Layup Parts

Machine Learning Engineer

Huntington Beach, CA · On-site

$120K - $185K/yr

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

Turion Space

Machine Learning Engineer

Irvine, CA · On-site

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 ...

Yum

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

... 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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... 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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

... 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 ...

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All JobsMachine Learning Engineer JobsJunior Machine Learning Engineer JobsJunior Machine Learning Engineer Jobs in Irvine, CA

Junior Machine Learning Engineer information

See Irvine, CA salary details

$36K

$77.1K

$117.5K

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

As of Aug 26, 2026, the average yearly pay for junior machine learning engineer in Irvine, CA is $77,069.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,100.00 and $85,900.00 per year, depending on experience, location, and employer.

What does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.
More about Junior Machine Learning Engineer jobs

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:

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For Junior Machine Learning Engineer jobs in Irvine, CA, the most frequently searched job titles are:

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

The top searched job categories for Junior Machine Learning Engineer jobs in Irvine, CA are:

What cities near Irvine, CA are hiring for Junior Machine Learning Engineer jobs?

Cities near Irvine, CA with the most Junior Machine Learning Engineer job openings:

Junior Machine Learning Engineer jobs near you
Infographic showing various Junior Machine Learning Engineer job openings in Irvine, CA as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 22% Part Time, and 1% Contract. Highlights an 89% Physical, 2% Hybrid, and 9% Remote job distribution, with an average salary of $77,069 per year, or $37.1 per hour.

Sr Machine Learning Engineer

Irvine, CA

Yum Brands
Traveler Accommodation • 10K+ employees

5.4

Company rating: 5.4 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

Recommended by parents

Respectful managers

Uninterrupted breaks

Learn more about Yum Brandsexternal

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 19 days ago

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. 

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