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Entry Level Machine Learning Engineer Jobs in Orange, CA

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 ...

New

Data Infrastructure Engineer

Los Angeles, CA · On-site

$115K - $151K/yr

Collaborate with data scientists and machine learning engineers to understand their computational and data needs and provide efficient solutions. * Stay up-to-date with the latest industry trends in ...

Showing results 41-60

Entry Level Machine Learning Engineer information

See Orange, CA salary details

$32K

$74.1K

$126.1K

How much do entry level machine learning engineer jobs pay per year?

As of Aug 20, 2026, the average yearly pay for entry level machine learning engineer in Orange, CA is $74,097.00, according to ZipRecruiter salary data. Most workers in this role earn between $55,000.00 and $83,900.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What are the key skills and qualifications needed to thrive as an entry level machine learning engineer?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in Orange, CA?

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

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Orange, CA?

For Entry Level Machine Learning Engineer jobs in Orange, CA, the most frequently searched job titles are:

What job categories do people searching Entry Level Machine Learning Engineer jobs in Orange, CA look for?

The top searched job categories for Entry Level Machine Learning Engineer jobs in Orange, CA are:

What cities near Orange, CA are hiring for Entry Level Machine Learning Engineer jobs?

Cities near Orange, CA with the most Entry Level Machine Learning Engineer job openings:

Infographic showing various Entry Level Machine Learning Engineer job openings in Orange, CA as of August 2026, with employment types broken down into 88% Full Time, 9% Part Time, and 3% Nights. Highlights an 97% In-person, and 3% Remote job distribution, with an average salary of $74,097 per year, or $35.6 per hour.

Senior Machine Learning Engineer

kinetic.auto

Costa Mesa, CA • On-site

$90 - $130/hr

Other

Medical, Dental, Retirement, PTO

Posted 2 days ago

New


Job description

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.
  • 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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