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Machine Learning Data Engineer Jobs in California

$160 - $190/hr

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 ...

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 ...

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 ...

Senior Data Engineer

Los Angeles, CA · On-site

$109K - $243K/yr

Build foundational data infrastructure that supports enterprise reporting, analytics, machine learning, data science, feature engineering, and AI-driven solutions. * Develop trusted, well-governed ...

Working at the intersection of data science and software engineering, you translate R&D and project ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Working at the intersection of data science and software engineering, you translate R&D and project ... This Role As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation ...

Build and maintain data pipelines and feature engineering workflows to support machinelearning and AI solutions * Design, train, evaluate, and refine machine learning models with minimal supervision ...

Showing results 41-60

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 Aug 10, 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.

Can a machine learning data engineer become a machine learning engineer?

A machine learning data engineer can transition to a machine learning engineer role by developing skills in model development, algorithms, and deployment, often requiring knowledge of programming languages like Python and frameworks such as TensorFlow or PyTorch. Gaining experience in building and deploying machine learning models is essential for this career progression.

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.

What is a machine learning data engineer?

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 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:
Infographic showing various Machine Learning Data Engineer job openings in California as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 12% Part Time, 2% Temporary, and 3% Contract. Highlights an 86% Physical, 4% Hybrid, and 10% Remote job distribution, with an average salary of $128,018 per year, or $61.5 per hour.

Machine Learning Engineer

jobs.frontdoordefense.com - Jobboard

Los Angeles, CA • On-site

$160 - $190/hr

Other

Posted 5 days ago


Job description

Machine Learning Engineer Lead end-to-end ML deployment for robotic sheet metal forming systems

Location: Los Angeles, California, United States

Compensation: $160,000 - 190,000 USD / year

Job Tags: Software

About The Role

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 machine learning models that power our robotic sheet metal forming systems. You'll work closely with our engineering team to transform raw data into actionable intelligence, enabling our robots to produce parts with greater precision, speed, and adaptability.

This is a hands‑on role for someone who thrives at the intersection of research and production, someone who is just as comfortable wrangling messy datasets as they are architecting scalable ML pipelines. If you're passionate about applying machine learning to real-world manufacturing challenges, we'd love to hear from you.

Key Responsibilities
  • Design, build, train, evaluate, and deploy machine learning models to support and improve our robotic manufacturing processes.
  • Identify, collect, clean, and organize data from diverse sources to construct high-quality datasets for model training and evaluation.
  • Develop and maintain scalable ML pipelines and infrastructure using cloud platforms, with a focus on Azure.
  • Leverage Databricks and Apache Spark for large-scale data processing and model development.
  • Collaborate with cross‑functional teams, including robotics, software, and manufacturing engineers to integrate ML solutions into production workflows.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well‑documented, and production‑quality Python code.
  • Communicate findings, results, and recommendations to both technical and non‑technical stakeholders.
Required Background & Experience
  • Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands‑on experience in machine learning and AI; or a Ph.D. in a relevant field with 3+ years of experience.
  • Strong experience designing, building, training, and testing machine learning models end‑to‑end.
  • Proven ability to work with raw, unstructured, or incomplete data, including data collection, cleaning, labeling, and dataset construction.
  • Proficiency in Python for ML development, data processing, and scripting.
  • Familiarity with cloud computing frameworks and services, with a preference for Microsoft Azure.
  • Experience with Databricks and Apache Spark for data engineering and model development.
Preferred Qualifications
  • Machine learning experience in CAD and computational geometry applications.
  • Experience working in the industrial or manufacturing space.
  • Experience with robotics, including robotic perception, control, or planning.

$160,000 - $190,000 a year The base salary range for this role is dependent on experience, qualifications, and overall alignment with the scope of the position. In addition to base compensation, Machina Labs offers a competitive benefits package and stock option participation.

Machina Labs is an affirmative action and equal employment opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law.

We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.

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