Staff/Senior Machine Learning Engineer, Search & Knowledge Platforms Santa Clara, California ... quantization, caching, distributed inference). * Experience with training and deploying machine ...
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Quick apply
Machine Learning Engineer
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$135K - $210K/yr
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Machine Learning Engineer Quantization information
See Seattle, WA salary details
$35.8K - $52.6K
1% of jobs
$52.6K - $69.4K
1% of jobs
$69.4K - $86.1K
5% of jobs
$86.1K - $102.9K
6% of jobs
$116.7K is the 25th percentile. Wages below this are outliers.
$102.9K - $119.6K
14% of jobs
$119.6K - $136.4K
14% of jobs
The median wage is $144.8K / yr.
$136.4K - $153.2K
18% of jobs
$153.2K - $169.9K
14% of jobs
$173.4K is the 75th percentile. Wages above this are outliers.
$169.9K - $186.7K
12% of jobs
$186.7K - $203.4K
11% of jobs
$203.4K - $220.2K
5% of jobs
$35.8K
$146.5K
$220.2K
How much do machine learning engineer quantization jobs pay per year?
What does a machine learning engineer quantization do?
What are some common challenges machine learning engineers face when implementing quantization techniques in production models?
What are the key skills and qualifications needed to thrive as a machine learning engineer quantization, and why are they important?
What is the difference between Machine Learning Engineer Quantization vs Data Scientist?
| Aspect | Machine Learning Engineer Quantization | Data Scientist |
|---|---|---|
| Required Credentials | Bachelor's or master's in CS, ML, or related; certifications in ML or AI | Bachelor's or master's in statistics, CS, or related; certifications in data analysis or statistics |
| Work Environment | Developing optimized ML models, deploying quantized models for efficiency | Analyzing data, building predictive models, interpreting results |
| Industry Usage | Tech companies, AI hardware firms, embedded systems | Finance, 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:
- Machine Learning Manager
- Principal Machine Learning Engineer
- Senior Staff Machine Learning Engineer
- Internship Aws Machine Learning
- Spacex Machine Learning
- Sr Machine Learning Engineer
- Machine Learning Engineer Two
- Freelance Google Machine Learning Engineer
- Senior Meta Machine Learning
- Remote Tensorflow Developer

Staff/Senior Machine Learning Engineer, Search & Knowledge Platforms
Seattle, WA • On-site
$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
Based on 684 frontline employees who took The Breakroom Quiz
6th of 30 rated technology retailers
Job description
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.
DescriptionAs 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.
- 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.
- 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.
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