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Machine Learning Engineer Quantization Jobs in Santa Ana, CA

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 ...

Motorola

Machine Learning Engineer

Los Angeles, CA · On-site

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 ...

Hadrian Automation

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Hadrian Automation

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do * Research, develop and deploy cutting-edge deep learning ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA

$160K - $250K/yr

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling these systems end to end. What You'll Do: * Research, develop and deploy cutting-edge deep learning ...

Yum! Brands

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

Senior Machine Learning Engineer We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This ...

Yum Brands

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Capgroup

Machine Learning Engineer II

Los Angeles, CA · On-site

$105K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

Capgroup

Machine Learning Engineer II

Irvine, CA · On-site

$104K - $143K/yr

In this role you will work with a high performing team of applied scientists, machine learning engineers, and software development engineers that has delivered a number of AI/ML systems to production ...

Yum!

Sr Machine Learning Engineer

Irvine, CA

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

Yum

Sr Machine Learning Engineer

Irvine, CA · On-site

$112K - $154K/yr

We are seeking a hands-on Senior Machine Learning Engineer to support and enhance machine learning platforms used for media measurement and customer analytics. This role partners closely with Data ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Santa Ana, CA

Machine Learning Engineer Quantization information

See Santa Ana, CA salary details

$32.8K

$134K

$201.4K

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

As of Jun 22, 2026, the average yearly pay for machine learning engineer quantization in Santa Ana, CA is $133,995.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,600.00 and $161,300.00 per year, depending on experience, location, and employer.

What are some common challenges Machine Learning Engineers face when implementing quantization techniques in production models?

Machine Learning Engineers working on quantization often encounter challenges such as balancing reduced model size and computational efficiency with maintaining acceptable accuracy levels. Adapting quantization methods to different hardware platforms can also require significant testing and optimization. Additionally, engineers must frequently address compatibility issues with existing deployment pipelines and ensure that quantization-aware training is properly integrated to minimize performance degradation. Collaboration with hardware and software teams is essential to streamline deployment and achieve optimal results.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer Quantization, and why are they important?

To thrive as a Machine Learning Engineer Quantization, you need a solid background in machine learning, deep learning, and computer science, typically supported by a degree in a related field. Familiarity with quantization techniques, frameworks such as TensorFlow Lite or PyTorch, and experience with hardware accelerators are crucial. Strong problem-solving skills, attention to detail, and effective collaboration set top performers apart. These capabilities are vital for efficiently deploying high-performing models on resource-constrained devices and ensuring scalable, real-world AI solutions.

What does a Machine Learning Engineer Quantization do?

A Machine Learning Engineer specializing in quantization focuses on optimizing machine learning models by reducing their size and computational requirements without significantly sacrificing accuracy. This involves converting model parameters and computations from high-precision formats (like 32-bit floating point) to lower-precision formats (such as 8-bit integers). Quantization enables faster inference, lower memory usage, and allows models to run efficiently on edge devices and mobile platforms. These engineers work closely with data scientists and hardware teams to implement, test, and validate quantized models in production environments.

What is the difference between Machine Learning Engineer Quantization vs Data Scientist?

AspectMachine Learning Engineer QuantizationData Scientist
Required CredentialsBachelor's or master's in CS, ML, or related; certifications in ML or AIBachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics
Work EnvironmentDeveloping optimized ML models, deploying quantized models for efficiencyAnalyzing data, building predictive models, interpreting results
Industry UsageTech companies, AI hardware firms, embedded systemsFinance, healthcare, marketing, research institutions

Machine Learning Engineer Quantization focuses on optimizing ML models for deployment efficiency, often working closely with hardware and software teams. Data Scientists analyze data and build models for insights. While both roles require ML knowledge, quantization engineers specialize in model compression techniques, whereas data scientists focus on data analysis and interpretation.

What are popular job titles related to Machine Learning Engineer Quantization jobs in Santa Ana, CA? For Machine Learning Engineer Quantization jobs in Santa Ana, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Santa Ana, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Santa Ana, CA are:
What cities near Santa Ana, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Santa Ana, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Machine Learning Engineer

Machine Learning Engineer

Machina Labs

Los Angeles, CA

Full-time

Posted 9 days ago

Job description

About Machina Labs
 
Engineering moves at software speed. Manufacturing doesn't. Yet.
 
Machina Labs is changing that. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By integrating advanced metal forming, robotics, and automated production inside a flexible factory architecture, we enable customers to move from prototype to production in weeks, not years.
 
Backed by Lockheed Martin, Toyota, and NVIDIA, we're building the manufacturing infrastructure that defense, aerospace, and advanced mobility programs will run on.
 
If you want to work on hard problems that matter and see them fly, drive, and defend, this is the place.    

Job Description:

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.
  • 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.
 

*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs.

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.

*This job description is not designed to cover or contain a comprehensive listing of activities, duties, or responsibilities required for this role. Duties and responsibilities may change based on business needs. 

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.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.