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Junior Machine Learning Engineer Jobs in Irvine, CA

Kinetic

Senior Machine Learning Engineer

Costa Mesa, CA · On-site

$112K - $154K/yr

You'll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$110K - $152K/yr

The Senior Machine Learning Platform Engineer will design and manage scalable ML infrastructure, develop cloud-based pipelines, and ensure the reliability of MLOps workflows while mentoring junior ...

Steg.AI

Machine Learning Scientist

Irvine, CA · On-site

$140 - $200/hr

# Machine Learning ScientistIrvine, CA**Full Time -- In Office -- Irvine, CA**## About Steg.AISteg.AI ... Collaborate with the engineering team to deploy models to customers* Benchmark new models versus ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Experience with machine learning libraries and modern frameworks such as PyTorch, Tensor flow, Keras, scikit-learn, etc. * Strong programming skills in MATLAB/Python/C/C++ and exposure to software ...

Masimo

Sr Engineer, AI/Machine Learning

Irvine, CA · On-site

$140K - $170K/yr

Experience with machine learning libraries and modern frameworks such as PyTorch, Tensor flow, Keras, scikit-learn, etc. * Strong programming skills in MATLAB/Python/C/C++ and exposure to software ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA

$112K - $154K/yr

... with learning systems proven in globally deployed solutions that deliver results today and get ... Mentor and manage junior engineers , providing technical guidance and career development. What You ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA · On-site

$112K - $154K/yr

... with learning systems proven in globally deployed solutions that deliver results today and get ... Mentor and manage junior engineers , providing technical guidance and career development. What You ...

FieldAI

Senior Machine Learning Platform Engineer

Irvine, CA

$112K - $154K/yr

... with learning systems proven in globally deployed solutions that deliver results today and get ... Mentor and manage junior engineers , providing technical guidance and career development. What You ...

3ds

AI/ML Developer

Long Beach, CA · On-site

$140K - $160K/yr

DASSAULT SYSTEMES is seeking an AI / Machine Learning Engineer to join our R&D organization. This individual will contribute to the design, development, and continuous improvement of generative AI ...

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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 Sep 3, 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.
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For Junior Machine Learning Engineer jobs in Irvine, CA, the most frequently searched job titles are:

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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.

Senior Machine Learning Engineer

Kinetic

Costa Mesa, CA • On-site

$112K - $154K/yr

Full-time

Medical, Dental, Retirement, PTO

Re-posted 26 days ago

Job description

About Kinetic
Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Kinetic aims to be the primary infrastructure-as-a-service for servicing future vehicles with our robotic repair centers, powered by our proprietary software and AI. We are a strong team of experienced robotics + automotive + shared mobility enthusiasts who have worked in self-driving, mapping, lidar, motorsport, and ride-sharing. We are a venture backed startup (Series B) with a clear go-to-market strategy and meaningful revenue.
About the role
You will be a part of a small, production-minded ML team based in Orange County/Oakland. You'll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.
Experience & Skills Required
  • Deep ML / CV Fundamentals: You need hands-on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry
  • Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs
  • AI-Empowered, Not AI-Dependent: We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension
  • Working knowledge of transformer and LLM building blocks applied to vision, including self-attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former)
  • Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multi-view geometry
  • Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers
  • Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred.
  • Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility

Responsibilities
  • The Work: Implement training loops, curate datasets, drive high-priority experiments, and partner with cross-functional teams to close feedback loops from edge cases
  • The Stack: PyTorch, Detectron2 / MMDetection / Segmentation, Hugging Face Transformers, Python (FastAPI), Docker, AWS
  • Collaborate on model development by implementing training loops, losses, augmentations, and evaluations using PyTorch
  • Keep current with the industry by summarizing relevant papers and PRs, and proposing small, testable improvements
  • Contribute to datasets by helping define labeling guidelines, curating splits, running quality checks, and maintaining data versioning
  • Run experiments to track metrics, perform ablations, write clear experiment notes, and present findings.
  • Provide production support by exporting models, writing basic inference code, adding tests, and assisting with performance profiling
  • Work cross-functionally, partnering with backend engineers on APIs, containers, and CI, and with ops/labeling teams on edge cases and feedback loops

Benefits
  • Competitive salary and equity package
  • Comprehensive health and dental insurance
  • Retirement savings plan.
  • Paid time off and holidays

Kinetic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.

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