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Machine Learning Engineer Quantization Jobs in Anaheim, CA

Hadrian

Machine Learning Engineer

Los Angeles, CA · On-site

As a Senior Machine Learning Engineer, you will play a key role in designing, building, and scaling advanced software systems to automate Design for Manufacturing analysis. Responsibilities : • ...

Machina Labs

Machine Learning Engineer

Los Angeles, CA · On-site

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 ...

Motorola

Machine Learning Engineer

Los Angeles, CA

$150K - $180K/yr

Bachelor degree with 4+ years experience as a machine learning engineer * AND 2+ years of Python and PyTorch or TensorFlow experience * Must be a U.S. citizen with the ability to obtain necessary ...

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 ...

HADRIAN

Machine Learning Engineer

Los Angeles, CA · On-site

$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

$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! 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 · 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 ...

Turion Space

Machine Learning Engineer

Irvine, CA

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML/CV solution that are integral to Turion's Space Domain Awareness data products. You will work on ...

Bespoke Labs

Machine Learning Engineer

Pomona, CA · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Anaheim, CA

Machine Learning Engineer Quantization information

See Anaheim, CA salary details

$33K

$134.8K

$202.6K

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

As of Jul 8, 2026, the average yearly pay for machine learning engineer quantization in Anaheim, CA is $134,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $162,300.00 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 Anaheim, CA? For Machine Learning Engineer Quantization jobs in Anaheim, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Anaheim, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Anaheim, CA are:
What cities near Anaheim, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Anaheim, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Anaheim, CA as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $134,809 per year, or $64.8 per hour.

Machine Learning Engineer

V-Work Infotech Solutions INC

Cerritos, CA • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary

We are seeking an experienced Machine Learning Engineer with 10+ years of software engineering or data engineering experience and strong expertise in designing, developing, deploying, and scaling machine learning solutions. The ideal candidate should have hands-on experience with Python, deep learning frameworks, MLOps, cloud platforms, data engineering, and Generative AI technologies.

The candidate will work closely with Data Scientists, AI Engineers, Data Engineers, and business stakeholders to build production-ready ML models and AI-powered applications.

Key Responsibilities
  • Design, build, and deploy machine learning models for production environments.
  • Develop predictive analytics, classification, regression, recommendation, and NLP models.
  • Build end-to-end ML pipelines for data ingestion, feature engineering, training, deployment, and monitoring.
  • Collaborate with Data Engineering teams to build scalable ML workflows.
  • Deploy ML models using Docker, Kubernetes, and cloud platforms.
  • Optimize model performance, scalability, and inference latency.
  • Implement CI/CD pipelines for machine learning (MLOps).
  • Work with structured and unstructured data from multiple sources.
  • Develop APIs for model serving and integration.
  • Monitor model drift, accuracy, and production performance.
  • Document technical designs and collaborate with cross-functional teams.

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