1

Machine Learning Engineer Quantization Jobs in Anaheim, CA

You'll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond ...

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

Engineer II, AI/Machine Learning

Irvine, CA · On-site

$120K - $150K/yr

The AI/Machine Learning Engineer II will be part of the R&D team at Masimo with focus on design and creation of next-generation health monitoring devices. It is a cutting-edge research and ...

Partner with executive leadership, engineering, product, and data science teams to ensure AI ... Solid proficiency in Python and deep learning frameworks (e.g., PyTorch, TensorFlow) * Experience ...

next page

Showing results 1-20

Machine Learning Engineer Quantization information

See Anaheim, CA salary details

$33K

$134.8K

$202.6K

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 Anaheim, CA is $134,809.00, according to ZipRecruiter salary data. Most workers in this role earn between $106,300.00 and $162,300.00 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Anaheim, CA? For Machine Learning Engineer Quantization jobs in Anaheim, CA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Anaheim, CA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Anaheim, CA are:
What cities near Anaheim, CA are hiring for Machine Learning Engineer Quantization jobs? Cities near Anaheim, CA with the most Machine Learning Engineer Quantization job openings:
Infographic showing various Machine Learning Engineer Quantization job openings in Anaheim, CA as of July 2026, with employment types broken down into 92% Full Time, 5% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $134,809 per year, or $64.8 per hour.

Senior Machine Learning Engineer

FieldAI

Irvine, CA

$180K - $215K/yr

Full-time

Posted 18 days ago


Job description

FieldAI's Irvine team is where embodied AI meets real robots, real sensors, and real field deployments. Based in the heart of Southern California's robotics ecosystem, we build risk-aware, reliable, field-ready AI systems that solve the hardest problems in robotics and unlock the full potential of embodied intelligence. If you want your work to ship, get tested on hardware, and improve through real deployments, Irvine is the place. We go beyond typical data-driven approaches or pure transformer-only architectures, combining rigorous engineering with learning systems proven in globally deployed solutions that deliver results today and get better every time our robots run in the field.

As an ML Engineer at FieldAI, you will help build the next-generation Field Foundation Model (FFM), powering a global fleet of autonomous robots deployed across diverse environments. Your contributions will directly shape how we scale - through advances in model architecture, training methodologies, and deployment strategies.

You'll collaborate closely with machine learning scientists, software engineers, and robotics experts to design and implement FFM capabilities that generalize across tasks and environments. Beyond model development, you'll also support deployment and monitoring to ensure smooth integration and reliable real-world performance.

This role offers the opportunity to work with cutting-edge technologies, solve complex challenges, and directly impact large-scale robot deployments.

What You'll Get To Do

Machine Learning modeling

  • Design, train, and deploy state-of-the-art machine learning models for end-to-end learning based navigation stack.
  • Work with deep learning architectures such as transformers, convolutional networks to capture complex decision making. 
  • Architect and implement full-stack end-to-end navigation solutions, covering perception, prediction, and planning.
  • Explore novel data generation and collection pipelines to enrich training datasets.

Model Deployment, Monitoring & Performance

  • Assist with deploying machine learning models into production environments
  • Continuously monitor models in production, detecting model drift, and automating retraining processes as applicable
  • Troubleshoot issues related to model deployment, performance, and system integration.
What You Have

Bachelor's or Master's degree in Computer Science, AI, Statistics, or a related field, with 4+ years of industry experience.

  • Proficiency in Python and modern ML frameworks such as PyTorch, TensorFlow, or JAX, alongside working knowledge of C++ for deployment and system integration.
  • Deep understanding of contemporary deep learning architectures, optimization, and evaluation, with a strong grasp of end-to-end navigation stack components - including perception, prediction, and path/motion planning.
  • Proven track record deploying ML models into production environments, ideally within robotics, self-driving, or NLP.
The Extras That Set You Apart
  • Publications in top tier ML or robotics conferences
$180,000 - $215,000 a year
Our salary range is generous and we consider each individual's background and experience when determining final compensation. Base pay may vary based on role scope, job-related knowledge, skills, experience, and the Irvine, California market.

Why Join FieldAI in Irvine?
In Irvine, you will work where the robots are. Our local team builds and tests systems on real hardware with real sensors, then ships them to operate in unstructured, previously unknown environments around the world. We are solving one of robotics' hardest challenges: reliable deployment outside the lab. Our Field Foundational Models raise the bar for perception, planning, localization, and manipulation, with an emphasis on explainability and safety for real-world use.
You will collaborate with a world-class team that thrives on creativity, resilience, and bold thinking. We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX, along with a track record of field deployments and strong performance in DARPA challenge segments.

Be Part of the Next Robotics Revolution
We are looking for builders who want their work to leave the whiteboard and show up on robots. If you enjoy tackling tough, uncharted questions and working across disciplines, you will find your people here. Our teams span AI, software, robotics engineering, product, field deployment, and technical communication, all focused on shipping systems that perform in the real world.

Our headquarters is in Irvine, and we partner closely with teams there as well as colleagues across the US and around the world. Join us in Southern California and help define what dependable, field-ready autonomy looks like.

We value diverse perspectives and are committed to fostering an inclusive workplace. We evaluate candidates and employees based on merit, qualifications, and performance, and we do not discriminate on the basis of race, color, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected statu
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
apply for this job