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Machine Learning Data Engineer Jobs in California

Sesame

Data Engineer, Machine Learning

San Francisco, CA · On-site

$170K - $240K/yr

You'll collaborate directly with machine learning engineers and researchers - your job is to make sure they have the right data, in the right shape, at the right time to train, evaluate, and ship ...

Full Scope

Data Engineer

San Francisco, CA

$134K - $162K/yr

Competitive We are looking for a skilled Data Engineer with a strong focus on AI and machine learning to join our dynamic team. The ideal candidate will play a critical role in designing ...

Adobe

Sr. Machine Learning Engineer 4

San Jose, CA · On-site

$122K - $168K/yr

Required : • Degree or 5 years of experience that is equivalent in practice • Demonstrated background in machine learning, data science, or a related area • Strong programming skills in Python ...

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 ... You'll work closely with our engineering team to transform raw data into actionable intelligence ...

Adobe

Machine Learning Engineer

San Jose, CA · On-site

Required : • Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a ... engineering principles • Excellent problem-solving and analytical skills, with a proactive ...

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All JobsMachine Learning Data Engineer JobsMachine Learning Data Engineer Jobs in California

Machine Learning Data Engineer information

See California salary details

$43.9K

$128K

$175.2K

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

As of Jun 28, 2026, the average yearly pay for machine learning data engineer in California is $128,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $135,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Machine Learning Data Engineer position, and why are they important?

To thrive as a Machine Learning Data Engineer, you typically need strong programming skills in Python or Scala, a deep understanding of data structures, algorithms, and machine learning concepts, as well as a degree in computer science or a related field. Experience with big data tools like Spark, Hadoop, and cloud platforms such as AWS or Azure, along with knowledge of data pipelines and ETL processes, is highly valuable; certifications in these areas can be advantageous. Problem-solving ability, attention to detail, and strong communication skills help professionals excel when working with diverse technical teams and stakeholders. These skills ensure data engineers can effectively build reliable, scalable data systems that support the development and deployment of machine learning models.

Can a data engineer become a machine learning engineer?

A data engineer can transition to a machine learning engineer role by gaining knowledge of machine learning algorithms, model development, and deployment techniques. Skills in programming languages like Python, experience with frameworks such as TensorFlow or PyTorch, and understanding of data pipelines are essential for this progression.

Which 5 jobs will survive AI?

Machine Learning Data Engineers are likely to continue to be in demand as AI advances because they develop and maintain the data pipelines and models essential for AI systems. Roles that require complex problem-solving, creativity, and human judgment, such as healthcare professionals, educators, skilled trades, and certain managerial positions, are also expected to persist despite AI automation. These jobs often involve tasks that are difficult for AI to replicate fully.

What is a Machine Learning Data Engineer job?

A Machine Learning Data Engineer is responsible for designing, building, and maintaining the data infrastructure that supports machine learning models. They develop data pipelines, ensure data quality, and optimize data storage for efficient processing. This role involves working with large-scale datasets, implementing ETL processes, and collaborating with data scientists to deploy machine learning models. Strong knowledge of databases, cloud platforms, and programming languages like Python and SQL is essential. Their work enables organizations to leverage machine learning effectively by providing reliable and scalable data solutions.

What are the typical daily responsibilities of a Machine Learning Data Engineer?

As a Machine Learning Data Engineer, your daily responsibilities often include designing, building, and maintaining data pipelines that efficiently move and transform data for machine learning applications. You may clean, preprocess, and validate large datasets, optimize storage solutions, and work closely with data scientists to ensure data is accessible and usable for model training and evaluation. Regular collaboration with software engineers and business analysts is common to align project goals and solve data-related challenges. Staying up to date with the latest tools and technologies is also important, as you'll help enable scalable and efficient deployment of machine learning solutions.

What engineers make $500,000?

Senior machine learning data engineers with extensive experience, advanced skills in data pipelines, cloud platforms, and machine learning frameworks can earn $500,000 or more annually, especially in high-cost-of-living areas or within large tech companies. Achieving this level typically requires a combination of technical expertise, leadership roles, and often stock options or bonuses.

Is ML a high paying job?

Machine Learning Data Engineers typically earn high salaries due to the specialized skills required, such as proficiency in programming, data modeling, and machine learning frameworks. Salaries vary by experience, location, and industry, but overall, the role is considered well-compensated within the tech field.
What are popular job titles related to Machine Learning Data Engineer jobs in California? For Machine Learning Data Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Data Engineer jobs in California look for? The top searched job categories for Machine Learning Data Engineer jobs in California are:
Machine Learning Data Engineer jobs near you

Machine Learning Engineer

Happy Elements

San Francisco, CA • On-site

Full-time

Posted 19 days ago

Job description

Machine Learning Engineer
Full-time
Responsibilities
  • Build, maintain, and improve efficient and reliable data mining and machine learning models.
  • Design, implement and tune machine learning models, and provide performance feedback.
  • Work closely with data engineers to adapt and improve data pipelines for production models.
  • Work closely with software engineers in putting models into production (interface, SLA, scalability).Qualifications
  • Strong academic background required. MS in Computer Science or Machine Learning with 2+ years of industry experience or PhD in related field with 1+ years of industry experience required.
  • Expert in Python, and computation graph toolkits (e.g., Scikit-learn, Tensorflow). Solid experience with Python packages such as Numpy, Panda, and Scikit-learn.
  • Expert/Master in common families of machine learning models, feature engineering, feature selection techniques, and tuning of machine learning models.
  • Master with SQL or other relational database.
  • Master in building and productionizing end-to-end machine learning systems.
  • Knowledge and experience in cloud computing is a plus.
  • Extensive data modeling and data architecture skills.
  • Advanced math skills (linear algebra, Bayesian statistics, group theory).
  • Ability to consistently exercise independent discretion and judgment on significant matters.
  • Strong analytical, problem-solving and communication skills.
  • Ability to work in a team environment

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