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Machine Learning Engineer Quantization Jobs in Seattle, WA

Machine Learning Engineer

Seattle, WA · On-site

$165K - $209K/yr

... data engineering, machine learning engineering, or related roles. * Data Pipelineexperience, designingand scaling data pipelines for unstructured or semi-structured data, including ingestion ...

Sr. Machine Learning Engineer

Seattle, WA · On-site

$118K - $163K/yr

PitchBook, a Morningstar company, is seeking a Senior Machine Learning Engineer to join their Product and Engineering team. The role involves delivering AI-powered features that extract insights from ...

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

$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 ...

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 ...

Sr. Machine Learning Engineer

Seattle, WA

$118K - $163K/yr

As a Senior Machine Learning Engineer (MLE) on the AI & ML (Insights) team, you will play a critical role in delivering AI-powered features that extract meaningful insights from PitchBook's wealth of ...

We are seeking a Principal Machine Learning Engineer to accelerate our training of generative models in close collaboration with Maching Learning (ML) researchers, software engineers, and domain ...

Senior Machine Learning Engineer

Bellevue, WA · On-site +1

$149K - $245K/yr

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Staff Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

At Chewy, our Sponsored Ads Technology team based out of Bellevue, WA is looking for a Senior Machine Learning Engineer to help launch various innovative ads-offerings for Chewy onsite and offsite ...

As a Machine Learning Engineer in the Machine Intelligence Neural Design (MIND) team, you will have an opportunity to be part of an ML innovation organization within Apple that has its roots in the ...

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Showing results 1-20

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 Jul 7, 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 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 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 Engineer

Machine Learning Engineer

Cisco

Seattle, WA • On-site

$165K - $209K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 6 days ago


Cisco Systems rating

8.0

Company rating: 8.0 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

48th of 141 rated electronics manufacturers


Job description

The application window is expected to close on: 07/31/2026

Job posting may be removed earlier if the position is filled or if a sufficient number of applications are received.

This is a hybrid role based out of Cisco's San Jose or Seattle office.

Meet the Team

The Cisco AI Research team is composed of AI research scientists, data scientists, and network engineers with deep subject matterexpertise. This diverse group collaborates on both foundational and applied research projects, driven by the challenge of connecting people and devicesata global scale. The team is newly formed and dynamic, blending AI and networking domain experts who work closely with engineers, product managers, and strategists experienced in AI and distributed systems.Members have the opportunity to shape the culture and direction of this growing team.

Your Impact

We are seeking a Machine LearningEngineertobuild dynamic troubleshooting agents thatdon'tjustmonitornetworks-they understand them. Our team is solving for the massive complexity of unstructured production log data, optimizing hardwareutilizationfor data collection, and automating the creation of synthetic datasets that push the boundaries of what LLMs can achieve in network configuration and remediation. Youwon'tjust bemaintainingpipelines,you will be architecting the data infrastructure that allows our models to reason through real-world network failures in real-time.

  • Design and scale automated pipelines that transform raw, high-velocity production logs into high-qualityinsights.

  • Developsystems that generate synthetic data, enabling our models to learn from edge cases that rarely occur in the wild.

  • Solvenetworkcomplexityproblemsbytackling theunique challenges of time and network state dependencies to improve the accuracy of our agents.

  • Optimizeatscalethroughefficient datacollection and hardwareutilization, ensuring our ML infrastructureremainsperformant as our agent capabilities expand.

  • Help shape thefuture of Network AIby collaboratingdirectly with researchers to define the next generation of AI-driven network management forCisco networkproductssuch asMeraki,ThousandEyes, Catalyst Centerand Nexus.

Minimum Qualifications

  • Bachelor's degree inSTEMand5+ years ofrelevant experience, orMaster'sdegree inSTEMand 3+ years of relevant experienceand or PhD inSTEM+0 years of relevantexperienceor equivalent related work experience

  • 5+ yearsof experience in data engineering, machine learning engineering, or related roles.

  • Data Pipelineexperience, designingand scaling data pipelines for unstructured or semi-structured data, including ingestion, cleansing, and auditing.

  • ML Infrastructure experienceworkingwith ML data workflows, including dataset creation, labeling, and evaluation.

  • Experience withPython and data processing frameworks (e.g., Spark, Beam, Ray).

  • Experience with ML systems and tools, such as training pipelines and model evaluation frameworks.

Preferred Qualifications

  • Experience with human-in-the-loop ML systems, active learning, weaksupervisionor self-evolving agents.

  • Exposurelarge language models, computer vision, or speech datasets.

  • Experience building internal tools or platforms used by annotation or operations teams.

Why Cisco?

At Cisco, we're revolutionizing how data and infrastructure connect and protect organizations in the AI era - and beyond. We've been innovating fearlessly for 40 years to create solutions that power how humans and technology work together across the physical and digital worlds. These solutions provide customers with unparalleled security, visibility, and insights across the entire digital footprint.

Fueled by the depth and breadth of our technology, we experiment and create meaningful solutions. Add to that our worldwide network of doers and experts, and you'll see that the opportunities to grow and build are limitless. We work as a team, collaborating with empathy to make really big things happen on a global scale. Because our solutions are everywhere, our impact is everywhere.

We are Cisco, and our power starts with you.

Message to applicants applying to work in the U.S. and/or Canada:The starting salary range posted for this position is $165,300.00 to $209,200.00 and reflects the projected salary range for new hires in this position in U.S. and/or Canada locations, not including incentive compensation*, equity, or benefits.

Individual pay is determined by the candidate's hiring location, market conditions, job-related skillset, experience, qualifications, education, certifications, and/or training. The full salary range for certain locations is listed below. For locations not listed below, the recruiter can share more details about compensation for the role in your location during the hiring process.

U.S. employees are offered benefits, subject to Cisco's plan eligibility rules, which include medical, dental and vision insurance, a 401(k) plan with a Cisco matching contribution, paid parental leave, short and long-term disability coverage, and basic life insurance. Please see the Cisco careers site to discover more benefits and perks. Employees may be eligible to receive grants of Cisco restricted stock units, which vest following continued employment with Cisco for defined periods of time.

U.S. employees are eligible for paid time away as described below, subject to Cisco's policies:

  • 10 paid holidays per full calendar year, plus 1 floating holiday for non-exempt employees

  • 1 paid day off for employee's birthday, paid year-end holiday shutdown, and 4 paid days off for personal wellness determined by Cisco

  • Non-exempt employees** receive 16 days of paid vacation time per full calendar year, accrued at rate of 4.92 hours per pay period for full-time employees

  • Exempt employees participate in Cisco's flexible vacation time off program, which has no defined limit on how much vacation time eligible employees may use (subject to availability and some business limitations)

  • 80 hours of sick time off provided on hire date and each January 1st thereafter, and up to 80 hours ofunused sick timecarried forwardfrom one calendar yearto the next

  • Additional paid time away may be requested to deal with critical or emergency issues for family members

  • Optional 10 paid days per full calendar year to volunteer

For non-sales roles, employees are also eligible to earn annual bonuses subject to Cisco's policies.

Employees on sales plans earn performance-based incentive pay on top of their base salary, which is split between quota and non-quota components, subject to the applicable Cisco plan. For quota-based incentive pay, Cisco typically pays as follows:

  • .75% of incentive target for each 1% of revenue attainment up to 50% of quota;

  • 1.5% of incentive target for each 1% of attainment between 50% and 75%;

  • 1% of incentive target for each 1% of attainment between 75% and 100%; and

  • Once performance exceeds 100% attainment, incentive rates are at or above 1% for each 1% of attainment with no cap on incentive compensation.

For non-quota-based sales performance elements such as strategic sales objectives, Cisco may pay 0% up to 125% of target. Cisco sales plans do not have a minimum threshold of performance for sales incentive compensation to be paid.

The applicable full salary ranges for this position, by specific state, are listed below:

New York City Metro Area:

$181,000.00 - $270,300.00

Non-Metro New York state & Washington state:

$165,300.00 - $240,600.00

* For quota-based sales roles on Cisco's sales plan, the ranges provided in this posting include base pay and sales target incentive compensation combined.

** Employees in Illinois, whether exempt or non-exempt, will participate in a unique time off program to meet local requirements.


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Benefits

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About Cisco Systems

Sourced by ZipRecruiter

Cisco Systems, a global tech titan based in San Jose, CA, US, operates in the information technology and services industry. Founded in 1984, the company was derived from a project between two computer scientists from Stanford University. They aimed to connect different networks of computer systems at the university, resulting in the first multi-protocol router, and subsequently, the birth of Cisco. As an industry-leading manufacturer of networking hardware and telecommunications equipment, Cisco's product and services range includes routers, switches, firewall devices, and telecommunication technology. The company's mission, "to shape the future of the Internet by creating unprecedented value and opportunity for our customers, employees, investors, and ecosystem partners," is a testament to its pursuit of technology-forward innovation and customer satisfaction.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1984

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