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Machine Learning Engineer Quantization Jobs in California

Machina Labs

Machine Learning Engineer

Chatsworth, CA

$160K - $190K/yr

Machine Learning Engineer Machina Labs is changing the way manufacturing works. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By ...

Apple

Machine Learning Engineer

Cupertino, CA · On-site

As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes at scale. You will work cross-functionally to bring innovative machine ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and graphics ...

Krea

Machine Learning Engineer

San Francisco, CA

Machine Learning Engineer At Krea, we are building next-generation AI creative tools. We are dedicated to making AI intuitive and controllable for creatives. Our mission is to build tools that ...

Apple

Machine Learning Engineer

Sunnyvale, CA · On-site

Apple's Video Computer Vision (VCV) Face and Body technologies team is looking for a skilled Machine Learning Engineer with experience developing ML models for computer vision and graphics ...

Poesis

Machine Learning Engineer

San Francisco, CA · On-site

$200K - $280K/yr

We're looking for an exceptional Machine Learning Engineer to help build the systems that make this possible. In this role, you'll develop models, signals and evaluation frameworks that power ...

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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 are popular job titles related to Machine Learning Engineer Quantization jobs in California? For Machine Learning Engineer Quantization jobs in California, the most frequently searched job titles are:
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:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in California as of June 2026, with employment types broken down into 100% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.
Machine Learning Engineer

Machine Learning Engineer

Machina Labs

Chatsworth, CA

$160K - $190K/yr

Other

Posted 7 days ago

Job description

Machine Learning Engineer

Machina Labs is changing the way manufacturing works. We build intelligent, software-defined factories that produce complex metal structures directly from digital design. By integrating advanced metal forming, robotics, and automated production inside a flexible factory architecture, we enable customers to move from prototype to production in weeks, not years.

If you want to work on hard problems that matter and see them fly, drive, and defend, this is the place.

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 machine learning models that power our robotic sheet metal forming systems. You'll work closely with our engineering team to transform raw data into actionable intelligence, enabling our robots to produce parts with greater precision, speed, and adaptability.

This is a hands-on role for someone who thrives at the intersection of research and production, someone who is just as comfortable wrangling messy datasets as they are architecting scalable ML pipelines. If you're passionate about applying machine learning to real-world manufacturing challenges, we'd love to hear from you.

Key Responsibilities:
  • Design, build, train, evaluate, and deploy machine learning models to support and improve our robotic manufacturing processes.
  • Identify, collect, clean, and organize data from diverse sources to construct high-quality datasets for model training and evaluation.
  • Develop and maintain scalable ML pipelines and infrastructure using cloud platforms, with a focus on Azure.
  • Leverage Databricks and Apache Spark for large-scale data processing and model development.
  • Collaborate with cross-functional teams, including robotics, software, and manufacturing engineers to integrate ML solutions into production workflows.
  • Stay current with the latest developments in machine learning and AI and evaluate their applicability to our manufacturing challenges.
  • Write clean, well-documented, and production-quality Python code.
  • Communicate findings, results, and recommendations to both technical and non-technical stakeholders.
Required Background & Experience:
  • Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a closely related field with 6+ years of hands-on experience in machine learning and AI; or a Ph.D. in a relevant field with 3+ years of experience.
  • Strong experience designing, building, training, and testing machine learning models end-to-end.
  • Proven ability to work with raw, unstructured, or incomplete data, including data collection, cleaning, labeling, and dataset construction.
  • Proficiency in Python for ML development, data processing, and scripting.
  • Familiarity with cloud computing frameworks and services, with a preference for Microsoft Azure.
  • Experience with Databricks and Apache Spark for data engineering and model development.
Preferred Qualifications:
  • Machine learning experience in CAD and computational geometry applications.
  • Experience working in the industrial or manufacturing space.
  • Experience with robotics, including robotic perception, control, or planning.

$160,000 - $190,000 a year The base salary range for this role is dependent on experience, qualifications, and overall alignment with the scope of the position. In addition to base compensation, Machina Labs offers a competitive benefits package and stock option participation.

Machina Labs is an Affirmative Action and Equal Employment Opportunity employer and considers all applicants for employment without regard to race, color, religion, sex, gender identity, gender expression, sexual orientation, national origin, age, disability, or status as a protected veteran in accordance with state and federal law.

We endeavor to make the job application process accessible to any and all users. If you have a disability that impacts your ability to complete the job application process and would like to request assistance or a reasonable accommodation, please contact us at (888)444-9777. This contact information is for accommodation requests only, not to inquire about the status of applications.

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