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Machine Learning Engineer Quantization Jobs in Los Angeles, CA

Sr Machine Learning Engineer

Irvine, CA ยท 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 ...

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 ...

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 ...

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 ...

... 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 ...

Senior Machine Learning Engineer

Burbank, CA

$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 ...

... 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 ...

Senior Machine Learning Engineer

Irvine, CA ยท On-site

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

... 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 ...

Senior Machine Learning Engineer

Los Angeles, CA ยท On-site

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

Senior Machine Learning Engineer

Los Angeles, CA ยท On-site

$112K - $154K/yr

Access on-demand professional development resources that allow you to hone existing skills and learn new ones "I can succeed as a Machine Learning Engineer at Capital Group" We are seeking a strong ...

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Machine Learning Engineer Quantization information

See Los Angeles, CA salary details

$33.9K

$138.8K

$208.5K

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

As of Jul 14, 2026, the average yearly pay for machine learning engineer quantization in Los Angeles, CA is $138,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,400.00 and $167,000.00 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 job categories do people searching Machine Learning Engineer Quantization jobs in Los Angeles, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Los Angeles, CA are:
What cities near Los Angeles, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Los Angeles, CA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer- Remote

Machine Learning Engineer- Remote

Harbor Freight Tools

Calabasas, CA โ€ข On-site, Remote

$110K - $166K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 25 days ago


Job description

The ML Engineer is responsible for the overall development, deployment, and support of our machine learning operations Harbor Freight. This includes the architecture and implementation of tools for model training, model monitoring, feature stores, model deployments, and model maintenance.
This role requires working with multiple levels of the organization, data science teams, application teams, security, software engineering, and business partners. It requires an experienced machine learning engineer with excellent business acumen, very strong technical skills, and data modeling / data warehousing expertise.
This position is technical and analytical in nature.
Duties and Responsibilities
  • Work closely with data scientists and IT in the development and implementation of our Enterprise AI platform. ย ย ย ย ย ย ย ย ย ย ย ย 
  • Build and maintain an industry leading MLOps tech stack. ย ย ย ย ย ย 
  • Mentor data scientists within the business, ensuring we're building best-in-class models. ย ย ย ย ย ย 
  • Optimize the scalability, performance, and reliability of our models by implementing best practices and leveraging industry-standard technologies. ย ย 
  • Streamline data ingestion, pre-processing, feature engineering, and model training workflows to improve efficiency and reduce latency. ย ย ย ย ย ย 
  • Design, build, and maintain a secure and scalable CI/CD framework for data science teams. ย ย ย ย ย ย ย ย ย ย ย ย 

Scope
  • Staff supervision and development:ย  No
  • Decision making:ย  Recommends policy and resolves problems
  • Travel:ย  Up to 5%
  • Flex Designation:ย  Anywhere

The anticipated salary range for this position is $110,800 - $166,100 depending on location, knowledge, skills, education and experience. This position is also eligible for an annual discretionary bonus. In addition, we offer comprehensive and competitive benefits to Associates (and their families) such as medical, dental, vision, life insurance, short-term and long-term disability. Eligible Associates are able to enroll in our company's 401k plan. Associates will accrue paid time off up to 236 hours per year (inclusive of PTO, floating holidays, and paid holidays). Paid sick time up to 80 hours per year unless otherwise required by law.