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Machine Learning Engineer Quantization Jobs in Seattle, WA

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

Senior Machine Learning Engineer

Seattle, WA · On-site

$139K - $183K/yr

This Senior Machine Learning Engineer role is part of the Distribution & Supply team which sits within our Technology division. The Distribution & Supply team builds and optimizes the machine ...

Staff Machine Learning Engineer In order to execute our vision, we need to grow our team of best-in-class machine learning engineers. We are looking for developers who are excited about staying at ...

As a Staff Machine Learning Engineer in Remitly's Core AI/ML team, you'll work at the heart of our AI strategy. The Core AI/ML team is responsible for building the foundational machine learning ...

We're looking for a Machine Learning Engineer to join Snap Inc! What you'll do: * Build and deploy machine learning models that power core products, serving millions of Snapchatters * Apply modern ML ...

Machine Learning Engineer

Seattle, WA · On-site

$150 - $200/hr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems , relating to training edge ML models on massive ...

As a Machine Learning Engineer specializing in knowledge graphs, you will work closely with cross-functional teams to design, implement, and optimize algorithms and models that enable efficient ...

Machine Learning Engineer

Seattle, WA · On-site

$135K - $210K/yr

We are looking for a Machine Learning Engineer to build creative, practical, and robust solutions to ML/CV software and infrastructure problems , relating to training edge ML models on massive ...

Showing results 41-60

Machine Learning Engineer Quantization information

See Seattle, WA salary details

$35.8K

$146.5K

$220.2K

How much do machine learning engineer quantization jobs pay per year?

As of Sep 9, 2026, the average yearly pay for machine learning engineer quantization in Seattle, WA is $146,543.00, according to ZipRecruiter salary data. Most workers in this role earn between $115,500.00 and $176,400.00 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 are popular job titles related to Machine Learning Engineer Quantization jobs in Seattle, WA?

For Machine Learning Engineer Quantization jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in Seattle, WA look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in Seattle, WA are:

Infographic showing various Machine Learning Engineer Quantization job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $146,543 per year, or $70.5 per hour.

Staff/Senior Machine Learning Engineer, Search & Knowledge Platforms

Seattle, WA • On-site

Apple Inc.
Computer and Electronic Product Manufacturing • 10K+ employees

$250/hr

Other

Medical, Dental, Retirement

Posted 10 days ago


Key responsibilities

  • Identify and address opportunities to improve the quality and performance of the search and ranking stack that powers world knowledge question answering.

  • Develop reliable, scalable ways to measure, assess, and compare the impact of different solutions on system quality and performance.

  • Communicate findings clearly to cross-functional teams and leadership, backing up recommendations with solid, rigorous data analysis.


Apple rating

8.1

Company rating: 8.1 out of 10

Based on 684 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers


Job description

Staff/Senior Machine Learning Engineer, Search & Knowledge Platforms

Santa Clara, California, United States Software and Services

The AI, Search & Knowledge Platforms team builds amazing products and services for Apple's customers while serving as a foundational partner to teams across Apple. The team delivers world-class AI, search, and knowledge systems powering Siri, Apple Intelligence, Safari, and iMessage, and operates the foundational platforms and infrastructure that keep these intelligent experiences running at hyperscale. As part of this group, you will focus on identifying and addressing opportunities to improve the quality and performance of the search and ranking stack that powers world knowledge question answering. This involves developing sophisticated machine learning systems, robust software heuristics, and large language models (LLMs) to understand user queries, retrieve and rank relevant documents, and provide users with direct answers that best satisfy their intent. You will work across the entire stack, applying a broad skill set that ranges from data science and opportunity analysis to ML system design, pipeline development, and quality evaluation.

Description

As a member of our fast-paced group, you will have the unique and rewarding opportunity to shape upcoming products from Apple. We are looking for a highly motivated and versatile Machine Learning and Software Engineer with a broad skill set. The ideal candidate combines strong engineering fundamentals with a keen product sense, and is a quick learner who is comfortable jumping into entirely new codebases and architectures. You must be an effective communicator and an adaptable problem solver, willing to take on whatever represents the optimal solution for the product, whether that means training machine learning models, writing robust software heuristics, or iterating on prompt engineering.

Responsibilities
  • Identify and address opportunities to improve the quality and performance of the search and ranking stack that powers world knowledge question answering.
  • Understand product requirements and apply a keen product sense to design engineering solutions that directly reflect our product vision.
  • Develop reliable, scalable ways to measure, assess, and compare the impact of different solutions on system quality and performance.
  • Leverage a versatile skill set encompassing data science, opportunity analysis, ML system design, pipeline development, and quality evaluation.
  • Navigate and contribute effectively to entirely new codebases and complex architectures.
  • Communicate findings clearly to cross-functional teams and leadership, backing up recommendations with solid, rigorous data analysis.
  • Learn quickly and adapt to the best technical approach for any given problem, seamlessly shifting between ML model training, software engineering, and prompt engineering.
Minimum Qualifications
  • Bachelor’s in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • 6+ years experience in shipping Search and ML systems
  • Strong programming skills in Python, Go or similar languages, with a solid foundation in software design, data structures, and algorithms.
  • Experience building scalable data pipelines and backend systems, coupled with the ability to quickly navigate and contribute to large, complex, and unfamiliar codebases.
  • Proficiency in data science methodologies, including A/B testing, statistical hypothesis testing and defining offline and online evaluation metrics for ML systems.
  • Experience with prompt engineering
  • Strong product sense with the ability to translate ambiguous product requirements into concrete engineering and modeling tasks.
  • Excellent communication skills, with the ability to back up decisions with rigorous data analysis and present findings clearly to cross-functional partners.
Preferred Qualifications
  • Master’s/Ph.D in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
  • 4+ years experience in shipping Search and ML systems
  • Hands-on experience in Information Retrieval, Search Ranking, or Natural Language Processing (NLP).
  • Demonstrated experience designing, building, or working with Retrieval-Augmented Generation (RAG) architectures and applications.
  • Familiarity with techniques for optimizing the inference performance, latency, and resource efficiency of LLMs and large machine learning systems in production environments (e.g., model quantization, caching, distributed inference).
  • Experience with training and deploying machine learning models

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $184,700 and $324,800, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976