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Machine Learning Engineer Quantization Jobs in National City, CA

General Atomics

Machine Learning Engineer

Poway, CA · On-site

We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous ...

Qualcomm

Senior Engineer - Machine Learning

San Diego, CA · On-site

$110K - $152K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: We are seeking ... Implement advanced techniques such as caching, quantization, batching, and routing * Benchmark and ...

Qualcomm

Senior Engineer - Machine Learning

San Diego, CA · On-site

$140.80 - $211.20/hr

Company Qualcomm Incorporated Job Area Engineering Group, Engineering Group > Machine Learning ... Implement advanced techniques such as caching, quantization, batching, and routing. * Benchmark and ...

Qualcomm

Senior Engineer - Machine Learning

San Diego, CA · On-site

$110K - $152K/yr

Engineering Group, Engineering Group > Machine Learning Engineering General Summary: We are seeking ... Implement advanced techniques such as caching, quantization, batching, and routing * Benchmark and ...

AbbVie

Machine Learning Engineer

San Diego, CA · On-site +1

Design, train, evaluate, and refine machine learning models with minimal supervision, applyingsound statistical and engineering practices * Implement ML solutions that can be deployed into production ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... quantization, pruning, and inference runtimes such as TensorRT or ONNX Runtime) * Strong ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... quantization, pruning, and inference runtimes such as TensorRT or ONNX Runtime) * Strong ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180 - $250/hr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... quantization, pruning, and inference runtimes such as TensorRT or ONNX Runtime) * Strong ...

Seasats

Senior Machine Learning Engineer

San Diego, CA · On-site

$180K - $250K/yr

Senior Machine Learning Engineer Location: San Diego, CA (in-office) Salary Range: $180,000 - $250 ... quantization, pruning, and inference runtimes such as TensorRT or ONNX Runtime) * Strong ...

The Marlin Alliance

Sr Machine Learning Engineer

San Diego, CA · On-site

$110K - $152K/yr

The Marlin Alliance, Inc. is seekinga talented and experienced Senior Machine Learning Engineer to join our team. The successful candidate will be expected to design, develop, and implement advanced ...

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in National City, CA

Machine Learning Engineer Quantization information

See National City, CA salary details

$32.3K

$132K

$198.3K

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 National City, CA is $131,958.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,000.00 and $158,800.00 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 National City, CA are hiring for Machine Learning Engineer Quantization jobs?

Cities near National City, CA with the most Machine Learning Engineer Quantization job openings:

Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

Poway, CA • On-site

General Atomics
Space Research Administration • 10K+ employees

9.0

Company rating: 9.0 out of 10

Based on 39 frontline employees who took The Breakroom Quiz

10th of 72 rated aerospace companies

Great coworkers

People enjoy working here

Good employer

Learn more about General Atomicsexternal

Full-time

Re-posted 15 days ago

Job description

Job Summary
General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.
We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions.
DUTIES AND RESPONSIBILITIES:
  • Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope.
  • In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.
  • In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code.
  • Completes programming and implements efficiencies, performs testing and debugging.
  • Completes documentation and procedures for installation and maintenance.
  • Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope.
  • Lead technical teams and scope challenging projects into executable sprints.
  • Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
  • Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution.
  • Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
  • Interface with external vendors and partners to integrate their technology into the team's autonomy stack.
  • Maintains the strict confidentiality of sensitive information.
  • Performs other duties as assigned.
  • Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices.
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Job Qualifications
  • Typically requires a bachelors or master's degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and two or more years of machine learning experience with a bachelors degree. May substitute equivalent machine learning engineer experience in lieu of education.
  • Must have an understanding of machine learning concepts, principles, and theory.
  • Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance.
  • Experience in developing and leading scalable software architectures from scratch.
  • Experience in optimizing AI models to meet edge processing requirements.
  • Strong coding skills in Java, Java Script, C/C++, Python
  • Experience in AI frameworks such as Tensorflow and pyTorch.
  • Excellent verbal and written communication skills.
  • Must be able to architect, design, and develop complex software.
  • Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
  • Active membership and participation in relevant conference and professional society organizations.
  • Demonstrated recent history of academic quality publications in the area of AI/ML and autonomy.
  • Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment.
  • Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience.
  • Must be able to work both independently and on a team.
  • Able to work extended hours as required.
  • Customer focused, must be able to work on a self-initiated basis and in a team environment, and able to work extended hours and travel as required.
  • Ability to obtain and maintain a DoD security clearance is required.
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About General Atomics

Sourced by ZipRecruiter

General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955

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