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Machine Learning Engineer Quantization information

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$30.6K

$125K

$187.9K

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

As of Jun 10, 2026, the average yearly pay for machine learning engineer quantization in Pittsburgh, PA is $125,011.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $150,500.00 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 Pittsburgh, PA? For Machine Learning Engineer Quantization jobs in Pittsburgh, PA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Pittsburgh, PA look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Pittsburgh, PA are:
What cities near Pittsburgh, PA are hiring for Machine Learning Engineer Quantization jobs? Cities near Pittsburgh, PA with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Machine Learning Engineer - Secure AI Lab with Security Clearance

Machine Learning Engineer - Secure AI Lab with Security Clearance

Software Engineering Institute

Pittsburgh, PA

Other

Posted 3 days ago

Job description

At the SEI AI Division, we conduct research in applied artificial intelligence and the engineering questions related to the practical design and implementation of AI technologies and systems. We currently lead a community-wide movement to mature the discipline of AI Engineering for Defense and National Security. As our government customers adopt AI and machine learning to provide leap-ahead mission capabilities, we * build real-world, mission-scale AI capabilities through solving practical engineering problems * discover and define the processes, practices, and tools to support operationalizing AI for robust, secure, scalable, and human-centered mission capabilities * prepare our customers to be ready for the unique challenges of adopting, deploying, using, and maintaining AI capabilities * identify and investigate emerging AI and AI-adjacent technologies that are rapidly transforming the technology landscape Are you creative, curious, energetic, collaborative, technology-focused, and hard-working? Are you interested in making a difference by bringing innovation to government organizations and beyond? Apply to join our team. Overview : As an Machine Learning Engineer, you will specialize in engineering solutions that support research into the vulnerabilities of AI and ML algorithms and securing against those vulnerabilities. The Secure AI Lab within the SEI's AI Division focuses on improving the security and robustness of AI systems. As part of the world-class research community at Carnegie Mellon University, the Secure AI Lab conducts and applies cutting-edge research to protect AI systems from adversaries who aim to manipulate the system to learn, do, or reveal something it isn't supposed to. The Secure AI Lab consists of machine learning research scientists, machine learning engineers, and software developers who work together to solve problems in the following areas: * Counter AI Research : Study threat models targeting AI and ML algorithms , understand the behaviors of AI algorithms, identify weak points, and design novel ways to subvert AI and ML systems . * AI and ML Algorithm Defense Research: Creat e practical mitigations and defenses for observed attacks affecting AI and ML algorithms and evaluate the effectiveness of defensive techniques . * Applied Adversarial Machine Learning: Advance the state of the art in adversarial machine learning by developing and transitioning capabilities to government sponsors. As an engineer, you will solve problems for government sponsors by analyzing, designing, and building responsible AI systems. Your day-to-day engineering tasks will include: * Identifying and i nvestigating emerging AI and AI-adjacent technologies. * Defining and r efining processes, practices, and tools for working with AI. * Designing and b uilding well-engineered prototypes of AI systems. * Transitioning and p roviding guidance on AI capabilities to government sponsors. Duties * Building Machine Learning Models and Systems: You will work with machine learning frameworks such as TensorFlow, PyTorch , Torch, and Caffe and modern programming languages including Python, C/C++, and Java. You will build and work with dat a pipelines, ETL processes, and backend systems. You will work with, extend, and implement state-of-the-art machine learning methods. * Technical Experimentation: You will experiment with modern and emerging machine learning frameworks, methods, and algorithms in application domains that include computer vision, natural language processing, planning and scheduling, robot control, and engineering safe, trusted, and reliable machine learning systems. * Test ing and evaluat ion . You'll conduct rapid prototyping to demonstrate and evaluate technologies in relevant environments. You'll evaluate systems for performance and security. You'll test capabilities using novel testing and analysis techniques. * Collaborat ion . You'll actively participate on teams of developers, researchers, designers, and technical leads. You'll collaborate with researchers and our government customers to understand challenges, needs, and possible solutions . * Mentoring. You'll contribute to improving the overall technical capabilities of the Division by mentoring and teaching others, participating in design (software and otherwise) sessions, and sharing insights and wisdom across the SEI. Knowledge and Experience * Comprehensive knowledge of machine learning ; previous experience in adversarial machine learning desirable but not required * A track record of using well-established engineering practices to solve difficult problems * An understanding of how to convert research results in to functioning prototypes or capabilities * Experience l ead ing technical projects in novel areas with limited previous work to build upon * Strong written and verbal communication skills ; able to convey complex technical ideas in a layperson's terms * Ample experience with publishing written or technical artifacts showcasing your work * Strong collaboration skills for working with colleagues and sponsors * Willing ness to guide and mentor junior team members Requirements * A bachelor's degree in computer science, statistics, machine learning, electrical engineering, or related discipline with eight (8) years of experience; OR MS in the same fields with one (1) year of experience; OR PhD in a relevant discipline with two (2) years of experience.
* Willingness to work onsite 5 days per week at SEI offices in Pittsburgh, PA or Arlington, VA. * You will be subject to a background investigation and must be able to obtain and maintain an active Department of War security clearance.
* Willing to travel up to 25% of the time to locations outside of your home location. Travel sites include SEI offices in Pittsburgh and Washington, D.C., sponsor sites, and conferences. Location
Arlington, VA, Pittsburgh, PA
Job Function
Software/Applications Development/Engineering
Position Type
Staff - Regular
Full time/Part time
Full time
Pay Basis
Salary
More Information: * Please visit " Why Carnegie Mellon " to learn more about becoming part of an institution inspiring innovations that change the world.
* Click here to view a listing of employee benefits
* Carnegie Mellon University is an Equal Opportunity Employer/Disability/Veteran .
* Statement of Assurance

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