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Machine Learning Engineer Quantization Jobs in Anaheim, CA

As a Senior Machine Learning Engineer, you will design, build, and scale advanced software systems that automate Design for Manufacturing analysis, leveraging deep learning and computer vision ...

Machine Learning Engineer

Los Angeles, CA · On-site

$150K - $180K/yr

Bachelor degree with 4+ years experience as a machine learning engineer * AND 2+ years of Python and PyTorch or TensorFlow experience * AND 2+ years of experience with RF signal processing * Must be ...

Machine Learning Engineer

Torrance, CA · On-site

$160K - $300K/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 ...

The Role We are seeking a Machine Learning Engineer to develop advanced models for extracting meaningful signals from multimodal time-series data. This role focuses on building robust, real-time ...

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 ...

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 ...

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

We're looking for a Machine Learning Engineer to train custom models using our internal data. This work spans design generation, cost estimation, evaluating the complexity and difficulty of a given ...

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 ...

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 ...

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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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 Sep 10, 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 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 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 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:

Infographic showing various Machine Learning Engineer Quantization job openings in Anaheim, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $134,809 per year, or $64.8 per hour.

Machine Learning Engineer

Los Angeles, CA • On-site

Full-time

Re-posted 8 days ago


Job description

ROLE SUMMARY 

The Machine Learning Engineer is a major contributor in driving our company's innovation and data-driven decision-making. By harnessing advanced analytics, machine learning, and big data technologies, this role directly impacts strategic business outcomes, revealing actionable insights and predicting trends that shape the future of our operations. Embedded at the intersection of data and strategy, the Data Scientist empowers the organization to navigate complex challenges, optimize performance, and unlock new growth opportunities. 

ESSENTIAL DUTIES 

Data and analysis 

  • Analyze public records and other real estate data using NLP and machine learning techniques to identify patterns and cluster entities. 
  • Develop methods for evaluating and selecting large language models (LLMs) for deployment. 
  • Build predictive models to identify potential borrowers, likelihood of default, and quality/valuations of properties for lending activities. 
  • Identify new business opportunities through tracking competitor trends and keeping management aware of developer lending market trends and insights. 
  • Assist in fostering a culture of test & learn within the company. 

Leadership  

  • Serve as analytics consultant to a broad variety of line-of-business teams. 
  • Partner with technology teams on product changes and impacts on data/performance. 
  • Mentor junior analysts on various data science techniques. 

 QUALIFICATIONS 

  • Bachelor's degree in quantitative field. 
  • 5-7 years of experience in analytical or consulting roles. 
  • Strong data science skills with AI/ML related Python libraries such as PyTorch, TensorFlow, and Keras. Conceptual knowledge of LLM's. 
  • Strong knowledge of statistics, hypothesis testing, and setting up experiments. 
  • Must have deployed several models to production. 
  • Exposure to data engineering skills. 
  • Strong communication and partnership skills, effective cross-department collaboration skills. 
  • Self-starter who can work under limited supervision. 
  • Mentoring skills to help develop junior analysts. 

WORK ENVIRONMENT 

  • This role works on-site from Ascent's Encino office 2 days per week 

THE PAY 

Salary range is $130,000-$150,000 per year, with a discretionary bonus of 20% per year.