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Machine Learning Engineer Quantization Jobs in Los Angeles, CA

... engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions ... Hands-on experience with model optimization (e.g., network quantization and mixed-precision ...

... engineering, or mathematics * 2-3 years of relevant experience in building deep learning solutions ... Hands-on experience with model optimization (e.g., network quantization and mixed-precision ...

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

Chatsworth, CA ยท On-site

$160K - $190K/yr

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 ...

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

Los Angeles, CA ยท 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 * Must be a U.S. citizen with the ability to obtain necessary ...

Machine Learning Engineer

Los Angeles, CA ยท On-site

$180 - $250/hr

Role Description Founding Data Scientist / Machine Learning Engineer We're looking for a highly ambitious Data Scientist to help build the predictive intelligence layer behind nowfluence. This is not ...

Machine Learning Engineer

Torrance, CA ยท 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 ...

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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 Aug 30, 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 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 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:

Senior Machine Learning Engineer - Hybrid schedule

Calance US

Los Angeles, CA โ€ข Hybrid

$112K - $154K/yr

Full-time

Medical, Dental, Vision, Life

Posted 4 days ago


Job description

We are hiring Senior Machine Learning Engineer - Hybrid schedule for a Full Time position in Los Angeles or NYC, CA
Sr. Machine Learning Engineer
About the Role
The Senior Machine Learning Engineer is an integral part of the Technology & Information Services team. This role will be responsible for the design, deployment, and optimization of custom workflows using classical machine learning (ML), Natural Language Processing (NLP), and Generative AI techniques to enhance legal and business processes, while designing, building, and optimizing custom machine learning models and workflows to optimize legal and business workflows. This role will be located in our Global Services Office. Please note that this role may be eligible for a flexible working schedule that allows for a hybrid and in-office presence.
Responsibilities & Qualifications
Other key responsibilities include:
Contributing to the entire lifecycle of AI/ML applications including concept, design, test, release, and support
Developing and maintaining robust ML pipelines for training, validation, and model deployment
Working with DevOps or infrastructure teams to manage GPU resources, model serving frameworks, and CI/CD workflows
Evaluating and integrating new research, tools, and frameworks to advance the team s capabilities
Developing ML/GenAI solutions in a professional manner, and in accordance with established deliverable schedules and firm procedures
Protecting and maintaining any highly sensitive, confidential, privileged, financial, and/or proprietary information that retains
We d love to hear from you if you:
Demonstrate proficiency with Python including experience with libraries and frameworks relevant to GenAI application development (e.g., LangChain)
Exhibit proficiency with ML frameworks (e.g., PyTorch, TensorFlow, Scikit-learn), and serving tools (e.g., TorchServe, ONNX, Triton)
Display proficiency in training or fine-tuning language models (e.g., BERT, Llama2, GPT), and their optimization (LoRA, knowledge distillation, pruning, and quantization)
And have:
A bachelor s degree and master s degree in information systems, computer science, engineering, data science, or a related field, preferably
A minimum of five (5) years of experience in industry roles focused on machine learning, applied AI, or data science
A minimum of five (5) years of Python industry experience
A minimum of three (3) years of experience working with agile teams
Experience building and productizing ML models and systems
Estimated Pay Range: 175-195K