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Machine Learning Engineer Jobs in Carson, CA (NOW HIRING)

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

$150K - $200K/yr

... rigorous engineering with learning systems proven in globally deployed solutions that deliver ... What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ...

Warnerbros

Senior Machine Learning Engineer

Burbank, CA · On-site

$111K - $153K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Carson, CA

Machine Learning Engineer information

See Carson, CA salary details

$32.9K

$134.7K

$202.4K

How much do machine learning engineer jobs pay per year?

As of Aug 21, 2026, the average yearly pay for machine learning engineer in Carson, CA is $134,670.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,200.00 and $162,100.00 per year, depending on experience, location, and employer.

What is a machine learning engineer?

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 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 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 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.

More about Machine Learning Engineer jobs

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Cities near Carson, CA with the most Machine Learning Engineer job openings:

Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Carson, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,670 per year, or $64.7 per hour.

Senior Machine Learning Engineer II

Rocket Lab Corporation

Long Beach, CA

$128K - $169K/yr

Full-time

Posted yesterday

New

Rocket Lab rating

9.2

Company rating: 9.2 out of 10

Based on 14 frontline employees who took The Breakroom Quiz

4th of 72 rated aerospace companies

Job description

SPACE SYSTEMS

At Rocket Lab, we're not just launching rockets - we're building the future of space. Our Space Systems team builds everything from complete spacecraft, precision payloads to the components and subsystems that allow them to thrive in space, like solar panels, flight software, star trackers, optical systems, separation systems, radios, and more.

Our Space Systems team has enabled more than 1,700 missions, ranging from interplanetary exploration, in-space manufacturing to national security and defense initiatives. The team has built spacecraft, payloads, and components for missions to the Moon and Mars, working with partners including NASA, the Space Development Agency, and the U.S. Space Force. Whether it's a single high-performance spacecraft, constellation, or the vertically integrated components that help them get to space - our world class Space Systems team is empowering some of the boldest and most ambitious space missions.

SENIOR MACHINE LEARNING ENGINEER II

Rocket Lab's Optical Systems division solves mission-critical space domain and Intelligence, Surveillance, and Reconnaissance (ISR) challenges for Department of Defense (DoD) and Intelligence Community (IC) customers. Our vision is to revolutionize the space-based payload market with innovative and novel designs for space, terrestrial, and airborne environments. Building on more than 20 years of electro-optical and infrared systems innovation, Optical Systems delivers solutions to the warfighter for responsive, scalable sensing solutions across all orbital domains.

As a Senior Machine Learning Engineer II based at our Optical Systems sites in Long Beach, CA, you will have the opportunity to support Tranche 3 of the U.S. Space Development Agency's (SDA) Proliferated Warfighter Space Architecture (PWSA) and beyond by building deep learning neural networks for advanced Electro-Optical (EO/IR) image processing.

WHAT YOU'LL DO

  • Contribute your experience to developing solutions for real-world problems.
  • Design, train, and deploy machine learning models for Optical Systems applications
  • Build and maintain ML pipelines for data ingestion, feature engineering, training, and inference.
  • Collaborate with other researchers/engineers on artificial intelligence, machine learning, and computer vision.
  • Preform rapid prototyping and enhanced development to be integrated into operational systems.
  • Perform troubleshooting, bug fixes, and maintenance of existing and new systems.
  • Stay current with ML research and evaluate new tools, frameworks, and techniques

 WHAT WE'RE LOOKING FOR IN A SENIOR MACHINE LEARNING ENGINEER II:

  • Bachelor's degree and 8+ years of experience, master's degree and 6+ years of experience, or a Ph.D. in Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Physics, or related field
  • Strong background in machine learning including model selection, architecting, training, validation, testing, and deployment
  • Experience in building deep learning neural network for computer vision, image processing, or video analysis (e.g., object detection, image segmentation, and tracking)
  • Strong math background, particularly linear algebra
  • Proficiency in Python
  • Experience with deep learning libraries (Keras, TensorFlow, Pytorch, etc)
  • Software engineering fundamentals: version control, testing, CI/CD, containerization
  • U.S. citizenship is required, due to program requirements
  • Ability to obtain and maintain an U.S. Government Security Clearance

NICE TO HAVE: 

  • Proficiency in C/C++/Rust
  • Experience curating quality, real-world datasets for training deep learning models
  • TS/SCI security clearance

This position may require prolonged periods of sitting, standing, walking, computer work, and occasional exposure to moderate levels of noise, dust, and fumes in production areas.

What Rocket Lab employees say

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