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Machine Learning Engineer Quantization Jobs in Sunnyvale, CA

Experience with quantization, distillation, or other model-optimization techniques for inference. Education * Master's or PhD in Computer Science, Electrical Engineering, or a related field, or ...

We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI ... Experience with quantization, distillation, or other model-optimization techniques for inference.

Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the ...

Our highly motivated Machine Learning Engineers work on these challenging problems and define solutions to directly impact various aspects of our core business. The Fulfillment group, within the ...

Machine Learning Engineer About Latent Health Healthcare today is only truly personalized for two groups: those with wealth and access, and those with physicians in their immediate family. For ...

Position Overview We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple ...

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging ...

Position: 2026 Machine Learning Engineer Req ID: Pending Location: San Jose Our Company Changing the world through digital experiences is what Adobe's all about. We give everyone-from emerging ...

Showing results 41-60

Machine Learning Engineer Quantization information

See Sunnyvale, CA salary details

$37K

$151.1K

$227.1K

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

As of Sep 10, 2026, the average yearly pay for machine learning engineer quantization in Sunnyvale, CA is $151,130.00, according to ZipRecruiter salary data. Most workers in this role earn between $119,100.00 and $181,900.00 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 Sunnyvale, CA?

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

What cities near Sunnyvale, CA are hiring for Machine Learning Engineer Quantization jobs?

Cities near Sunnyvale, CA with the most Machine Learning Engineer Quantization job openings:

Principal Machine Learning Engineer

San Francisco, CA • On-site

Adobe
Computer and Computer Peripheral Equipment and Software Wholesalers • 10K+ employees

Full-time

Posted 24 days ago


Key responsibilities

  • Lead the development of core GenAI services and APIs that integrate generative models into Adobe's products.

  • Architect ML serving workflows for model deployment, customization, and ecosystem integration, including fine-tuning flows.

  • Co-develop and optimize GPU-accelerated inference pipelines focusing on latency, throughput, scalability, and reliability.


Adobe rating

8.9

Company rating: 8.9 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

The Opportunity

Firefly Foundry is Adobe's enterprise managed-service offering for custom multimedia generative AI - deep-tuned image, video, and 3D models built on each customer's IP, paired with creative production workflows and a media-intelligence layer, and deployed across new and existing Adobe surfaces and products, including Firefly, Photoshop, Illustrator, Express, Stock, and Premiere.

We are hiring a Principal Machine Learning Engineer to serve as the technical lead for our GenAI Services area. This is not a model-training or research role - it is the senior-most hands-on engineering authority over how our generative models are architected,optimized, and served at enterprise scale. You will set the inference architecture and technical standards that a growing organization of engineers builds against, co-develop and optimize the inference code that makes those systems fast and cost-efficient, and architect the APIs and product backend that let Adobe's first-party and third-party models reach both internal applications and external plugin integrations. Where the Director owns the multi-year technical strategy, headcount, and company roadmap for the org, you own the architecture, technical depth, and hands-on execution that make that strategy real - spanning multiple engineering teams without owning their people management.

What this role owns

  • The technical architecture for composing,optimizing, and serving heterogeneous generative model pipelines - LLMs, diffusion and transformer-based image/video models, RAG and retrieval systems, multi-turn agentic flows, and 3D/mesh pipelines - across the GenAI Services area.

  • The optimization strategy for inference performance: latency, throughput, and cost-to-serve across model families and GPU fleets.

  • The system design standards for pipeline composition, multi-tenant serving, and the product backend/API and plugin surface that integratesfirst-partyand third-party generative models into Adobe's flagship products.

  • Technical direction across multiple engineering teams as the principal authority on architecture and design - a cross-team scope, distinct from the Director's org-wide roadmap andmanagementownership.

Who you will partner with

  • Applied Science- to translate research models and emerging techniques into production-grade inference architecture.

  • Director, ML Engineering and ML Engineering leadership-to aligntechnical architecture with organizational strategy and priorities.

  • Product Managers and TPMs- to define and deliver against the roadmap for GenAI services and APIs.

  • Firefly Foundry Studio and AI Platform- to translate creative production workflows into performant services and toalign onshared infrastructure and serving primitives.

What you will do

  • Lead the development of core GenAI services and APIs that integrate a wide range of first-party and third-party generative models into Adobe's flagship products.

  • Architect MLservingworkflows for enterprise-scale model customization, deployment, and ecosystem integration - including externalizable, self-serve fine-tuning flows.

  • Co-develop andoptimizeGPU-accelerated inference pipelines - prioritizing latency, throughput, scalability, and reliability - using tools such asPyTorch, CUDA, Triton, andTensorRT.

  • Design andarchitectthe product backend and plugin ecosystem that lets internal applications and external integrations consume Firefly Foundry's model services.

  • Provide hands-on technical leadership: guide engineers through architecture, design, implementation, and best practices, and mentor a growing organization of ML engineers.

  • Research and evaluate emerging inference andMLOpstechnologies - serving runtimes, quantization, GPUscheduling - to improve engineering velocity and system performance.

  • Lead design reviews and set technical standards, ensuring high reliability and maintainability across systems.

  • Drive cross-functional alignment with Product Managers, TPMs, and engineering leaders to define and deliver on the roadmap.

  • Foster a culture of technical excellence and continuous improvement across the organization.

What you bring

  • MS or PhD in Computer Science, Machine Learning, or a related field - or equivalent industry experience.

  • 8+ years of experience in machine learning engineering, including production-scale deployment and serving - not training or research experimentation.

  • 3+ years leading the technical direction of large-scale, GPU-intensive GenAI inference systems - serving, architecture, and optimization.

  • Deep experience with inference frameworks and tools such asPyTorch, CUDA, Triton,TensorRT, Nvidia Dynamo, and Python.

  • Strong understanding of generative model architectures - diffusion models, transformers, GANs, LLMs - sufficient to make architecture and optimization calls and reasonaboutoutput quality, in partnership with Applied Science.

  • Proven experience architecting multi-model pipelines and serving them behind APIs at enterprise scale.

  • Experience designing product backend systems and plugin architectures consumed by internal applications and external integrations.

  • Proven success leading cross-functional teams through complex, high-stakes technical initiatives, witha track recordof driving alignment in matrixed organizations.

  • Excellent communication and technical leadership skills.

Preferred Qualifications

  • Experience with model serving, orchestration, and GPU resource management in large-scale environments.

  • Hands-onexpertisein Kubernetes, distributed systems, andMLOpsplatforms.

  • Experience with RAG architectures and multi-turn, agentic conversational systems.

  • Experience with quantization, distillation, or other model-optimization techniques for inference.

Education

  • Master's or PhD in Computer Science, Electrical Engineering, or a related field, or equivalent practical experience building and leading production-scale ML systems.

#FireflyGenAI


About Adobe

Adobe empowers everyone to create through innovative platforms and tools that unleash creativity, productivity and personalized customer experiences. Adobe's industry-leading offerings including Adobe Acrobat Studio, Adobe Express, Adobe Firefly, Creative Cloud, Adobe Experience Platform, Adobe Experience Manager, and GenStudio enable people and businesses to turn ideas into impact, powered by AI and driven by human ingenuity.


Our 30,000+ employees worldwide are creating the future and raising the bar as we drive the next decade of growth. We're on a mission to hire the very best and believe in creating a company culture where all employees are empowered to make an impact. At Adobe, we believe that great ideas can come from anywhere in the organization. The next big idea could be yours.


Let's Adobe together

At Adobe, we believe in creating a company culture where all employees are empowered to make an impact. Learn more about Adobe life, including our values and culture, focus on people, purpose and community, Adobe for All, comprehensive benefits programs, the stories we tell, the customers we serve, and how you can help us advance our mission of empowering everyone to create.


Adobe is proud to be an Equal Employment Opportunity employer. We do not discriminate based on gender, race or color, ethnicity or national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status, or any other protected characteristic. Learn more.


Adobe aims to make our Careers website and recruiting process accessible to any and all users. If you have a disability or special need that requires accommodation to navigate our website or complete the application process, email accommodations@adobe.com.


AI Use Guidelines for Interviews:
Our interviews are designed to reflect your own skills and thinking. The use of AI or recording tools during live interviews is not permitted unless explicitly invited by the interviewer or approved in advance as part of a reasonable accommodation. If these tools are used inappropriately or in a way that misrepresents your work, your application may not move forward in the process.


At Adobe, we empower employees to innovate with AI - and we look for candidates eager to do the same. As part of the hiring experience, we provide clear guidance on where AI is encouraged during the process and where it's restricted during live interviews. See how we think about AI in the hiring experience.

Expected Pay Range:

Our compensation reflects the cost of labor across several U.S. geographic markets, and we pay differently based on those defined markets. The U.S. pay range for this positionis $206,400 -- $379,100 annually. Paywithin this range varies by work locationand may also depend on job-related knowledge, skills,and experience. Your recruiter can share more about the specific salary range for the job location during the hiring process. In California, the pay range for this position is $261,800 - $379,100 In Washington, the pay range for this position is $242,600 - $351,225

At Adobe, for sales roles starting salaries are expressed as total target compensation (TTC = base + commission), and short-term incentives are in the form of sales commission plans. Non-sales roles starting salaries are expressed as base salary and short-term incentives are in the form of the Annual Incentive Plan (AIP).

In addition, certain roles may be eligible for long-term incentives in the form of a new hire equity award.

State-Specific Notices:

California:

Fair Chance Ordinances

Adobe will consider qualified applicants with arrest or conviction records for employment in accordance with state and local laws and "fair chance" ordinances.

Colorado:

Application Window Notice

If this role is open to hiring in Colorado (as listed on the job posting), the application window will remain open until at least the date and time stated above in Pacific Time, in compliance with Colorado pay transparency regulations. If this role does not have Colorado listed as a hiring location, no specific application window applies, and the posting may close at any time based on hiring needs.

Massachusetts:

Massachusetts Legal Notice

It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.


What Adobe employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Adobe logo

About Adobe

Sourced by ZipRecruiter

Adobe for All is our vision to advance diversity, equity, and inclusion (DEI) across our company and in our communities. We’re focused on creating a more diverse and inclusive workforce; unleashing the full potential of every employee; and driving meaningful impact for Adobe, our industry, and society at large. Creativity has the power to unite us and inspire us to change the world. Through a vision we call Creativity for All, we’re empowering millions of people of all ages and backgrounds to express themselves, reach their full potential, and share their diverse perspectives with the world. We’re committed to advancing the responsible use of technology and driving a positive environmental impact through sustainability and climate action. Our innovations are making a significant impact across AI ethics, security, privacy, trust and safety, accessibility, and sustainability.

Industry

Computer and computer peripheral equipment and software wholesalers

Company size

10,000+ Employees

Headquarters location

San Jose, CA, US

Year founded

1982