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Machine Learning Engineer Jobs in California (NOW HIRING)

Advantest

Machine Learning Engineer

San Jose, CA

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you ...

DocuSign

Machine Learning Engineer

San Francisco, CA · On-site +1

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Abaka AI

Machine Learning Engineer

Mountain View, CA · On-site

They are seeking a Machine Learning Engineer to design and develop scalable training pipelines for multimodal AI systems, collaborating with data engineering and research teams to drive the technical ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer on our core AI/ML team, you will design and build GenAI-powered features and workflows leveraging LLMs and modern AI techniques. You will collaborate closely with ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

Apple

Machine Learning Engineer (Search)

Cupertino, CA · On-site

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Machina Labs

Machine Learning Engineer

Chatsworth, CA · On-site

$160K - $190K/yr

We are looking for a Machine Learning Engineer to join our team and help us push the boundaries of what's possible in smart manufacturing. In this role, you will design, build, train, and deploy ...

Adobe

Machine Learning Engineer

San Jose, CA

As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...

Docusign

Machine Learning Engineer

San Francisco, CA · On-site

$164K - $266K/yr

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

Hive

Machine Learning Engineer

San Francisco, CA · On-site

$120K - $180K/yr

Machine Learning Role In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at the ...

Apple

Machine Learning Engineer

San Diego, CA · On-site

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

Apple

Machine Learning Engineer

Cupertino, CA

$212K - $318K/yr

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

Motorola

Machine Learning Engineer

Los Angeles, CA

THE OPPORTUNITY Silvus is seeking a Machine Learning Engineer who will report to the R&D Director, Machine Learning on the R&D team. The successful individual in this role will focus on applying ...

Nace AI

Machine Learning Engineer

Palo Alto, CA

As a Machine Learning Engineer, you will play a central role in translating cutting-edge machine learning research into scalable, production-ready solutions. You will collaborate closely with cross ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in California

Machine Learning Engineer information

See California salary details

$31.1K

$127.1K

$191K

How much do machine learning engineer jobs pay per year?

As of Jun 8, 2026, the average yearly pay for machine learning engineer in California is $127,083.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,200.00 and $153,000.00 per year, depending on experience, location, and employer.

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.

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.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What are the most commonly searched types of Machine Learning Engineer jobs in California? The most popular types of Machine Learning Engineer jobs in California are:
What are popular job titles related to Machine Learning Engineer jobs in California? For Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in California look for? The top searched job categories for Machine Learning Engineer jobs in California are:
What cities in California are hiring for Machine Learning Engineer jobs? Cities in California with the most Machine Learning Engineer job openings:
What are popular job titles related to Machine Learning Engineer jobs in CA? For Machine Learning Engineer jobs in CA, the most frequently searched job titles are:
Machine Learning Engineer jobs near you

Machine Learning Engineer

Advantest

San Jose, CA

Full-time

Posted 13 days ago

Job description

Advantest is seeking a motivated Junior Machine Learning Engineer to support the development of datadriven and MLpowered solutions for semiconductor R&D, test, and operations teams. In this role,you'llcontribute to building predictive models, conducting statistical analyses, andassistingin the development of lighttomoderate data pipelines that help transform complex semiconductor datasets into actionable insights.

This position is ideal for a recent graduate with strong foundational ML skills whoiseager to learn, collaborate, and grow in a fastpaced, technically rich environment.You'llwork alongside experienced engineers, data scientists, and domain experts while gaining handson experience across the ML lifecycle-from data preparation to model deployment

Key Responsibilities

Machine Learning & Advanced Analytics

  • Develop and evaluate ML models (e.g., classification, anomaly detection, regression, timeseries analysis).
  • Perform feature engineering andexploratorydata analysis on semiconductor datasets.
  • Contribute to model deployment workflows in collaboration with MLdata scientists, followingMLOpsbest practices.
  • Assistin implementing model monitoring, retraining workflows, and documentation.
  • Experiment with modern analytics techniques, including LLMbased or generativeAI methods, under guidance from senior team members.

Data Engineering & Pipeline Support

  • Help build and maintain ETL/ELT workflows that prepare data for analysis and modeling.
  • Support data quality checks, versioning, and data validation tasks.
  • Work with cloudand onpremtools to help ensure data accessibility for ML applications.

CrossFunctional Collaboration

  • Work with semiconductor engineers and data scientists to translate domain challenges into analytical tasks.
  • Support the creation of dashboards, reports, and visualizations that communicate insights clearly.
  • Learn and apply semiconductorspecific data concepts with the support of senior mentors.

Apply