1

Machine Learning Engineer Quantization Jobs in California

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 : • ...

As a Machine Learning Engineer, you'll be an integral part of building out the state-of-the-art AI intelligence engine and applications for the food industry. Responsibilities : • Leverage cutting ...

As a Machine Learning Engineer at Atoms, you'll be an integral part of building out the state-of-the-art AI intelligence engine and applications for the food industry. Responsibilities : • Leverage ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

The Opportunity Adobe is looking for a Machine Learning Engineer who will apply AI and machine learning techniques to big-data problems to help Adobe better understand, lead and optimize the ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

We are looking for a Machine Learning Engineer to join and play a big part in the next revolution of Maps; to enable users to find more things in innovative ways. On our team, you will have plenty of ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

They are seeking a Machine Learning Engineer to contribute to the development of tools and infrastructure for interpretable AI systems, playing a key role in transforming research into usable product ...

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 ...

On-Device Machine Learning Engineer

Sunnyvale, CA · On-site

$164K/yr

We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our ... Strong knowledge of model compression techniques such as pruning, distillation, quantization and ...

As a Machine Learning Engineer, you will play a key role in developing machine learning models and algorithms. Our team is dedicated to solving complex business challenges through innovative machine ...

We are looking for a highly motivated and skilled Machine Learning Integration Engineer to join our ... Strong knowledge of model compression techniques such as pruning, distillation, quantization and ...

What you'll do As a Machine Learning Engineer on the AI Platform team, you will design and build the foundational infrastructure that powers Docusign's next generation of intelligent systems. You ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

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 California look for? The top searched job categories for Machine Learning Engineer Quantization jobs in California are:
What cities in California are hiring for Machine Learning Engineer Quantization jobs? Cities in California with the most Machine Learning Engineer Quantization job openings:
Infographic showing various Machine Learning Engineer Quantization job openings in California as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Hadrian

Los Angeles, CA • On-site

Full-time

Re-posted 6 days ago


Job description

Job Summary:
Hadrian is building autonomous factories that help aerospace and defense companies manufacture rockets, satellites, jets, and ships. 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:
• Research, develop and deploy cutting-edge deep learning models, including OCR, vision-language, and detection models for document understanding and layout analysis
• Contribute to the ongoing development and refinement of current models in close collaboration within the engineering team and end users
• Work in every facet of the Machine Learning lifecycle - including the creation and optimization of production data pipelines, and software systems for training, inference, labeling, and evaluation
• Judiciously combine open-source solutions and novel research to create world-class vision systems for manufacturing applications
Qualifications:
Required:
• Bachelors in Computer Science, Electrical Engineering, Mechanical Engineering (or similar discipline), or an equivalent amount of deep learning experience
• 5+ years of experience in Computer Vision and/or Machine Learning, including ownership of projects throughout the entire ML Lifecycle
• Proficiency in Python, OpenCV, SQL, and one or more deep learning frameworks (PyTorch, Tensorflow, etc.)
Preferred:
• A Master’s Degree in Computer Science with focus in Artificial Intelligence or Machine Learning
• Demonstrated experience with detection/segmentation models and achieving high performance results - including exploratory analysis, model selection, and hyperparameter tuning
• Previously worked in aerospace, defense, or manufacturing, and have experience working 3D/CAD/CAM data for manufacturing applications
• Strong software engineering skills and prior web development experience using Javascript/TypeScript or Python, and familiarity with FastAPI or Express frameworks
• Prior experience with distributed training using cloud infrastructure
• Prior experience with visual document understanding and layout analysis
• Published research or achieved SOA results on an ML application
• Prior experience with multi-modal deep learning models
• You have a passion for manufacturing and believe that the industry needs better software
• Prior experience working in a startup environment
Company:
Hadrian builds AI-powered automated factories that manufacture precision parts for defense, aerospace, and space industries. Founded in 2020, the company is headquartered in Hawthorne, USA, with a team of 201-500 employees. The company is currently Growth Stage.