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Machine Learning Engineer Quantization Jobs in Raleigh, NC

ExtendMyTeam

Machine Learning Engineer

Cary, NC

Position Summary We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual ...

CoVar

Machine Learning Engineer

Durham, NC

Machine Learning Engineer About CoVar CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. We develop AI/ML tools to help the ...

Vadum, Inc.

Machine Learning Engineer

Raleigh, NC · On-site

$96K - $137K/yr

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC · On-site

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Vadum Inc

Machine Learning Engineer

Raleigh, NC

We are seeking a talented and innovative Machine Learning Engineer to join our dynamic team. In this role, you will be responsible for designing and developing machine learning prototypes, as well as ...

Q2 Software, Inc.

Machine Learning Engineer

Cary, NC · On-site

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

Q2

Machine Learning Engineer

Cary, NC

As a Machine Learning Engineer, you will help build and operate production systems that power our fraud products. You'll work closely with data scientists and engineers to bring models into ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

RELX Group plc

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

LexisNexis

Machine Learning Engineer Lead

Raleigh, NC

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

RELX

Machine Learning Engineer Lead

Raleigh, NC · On-site

$115.40K - $192.30K/yr

We are seeking a Machine Learning Engineer Lead to design, build, and operate scalable AI/ML systems and agentic architectures that support next-generation legal research and analytics products. This ...

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$71.10K - $96.20K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

OptiTrack

Machine Learning & Operations Engineer

Durham, NC · Remote

$67.20K - $90.80K/yr

About the Role OptiTrack is seeking a Machine Learning Engineer to help design, automate, and scale an MLOps system and provide other support to teams working on projects involving machine learning.

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All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Raleigh, NC

Machine Learning Engineer Quantization information

See Raleigh, NC salary details

$30.6K

$125.2K

$188.1K

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

As of May 30, 2026, the average yearly pay for machine learning engineer quantization in Raleigh, NC is $125,174.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,700.00 and $150,700.00 per year, depending on experience, location, and employer.

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 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 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 Raleigh, NC? For Machine Learning Engineer Quantization jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Raleigh, NC look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Machine Learning Engineer Quantization jobs? Cities near Raleigh, NC with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Machine Learning Engineer

ExtendMyTeam

Cary, NC

Full-time

Posted 11 days ago

Job description

Join a high-growth financial technology organization focused on building modern digital banking, payments, lending, and risk solutions for financial institutions and fintech partners. This team is investing in machine learning and analytics capabilities to help improve fraud detection, predictive insights, and operational decision-making across customer-facing products.

This is an opportunity to work on applied machine learning systems that directly support real-world fraud and risk workflows. The team owns solutions end-to-end and is focused on building scalable, production-ready ML applications that deliver measurable customer impact.

Position Summary

We are seeking a Machine Learning Engineer to help design, deploy, and support production machine learning systems within a collaborative engineering organization. This individual will work closely with software engineers, data scientists, and product teams to operationalize machine learning models, improve ML infrastructure, and support scalable analytics workflows.

This is a hands-on engineering role focused on production systems, model deployment, APIs, pipelines, and ML operations rather than purely research-oriented machine learning work.

Responsibilities

  • Build and maintain systems and pipelines supporting machine learning training, evaluation, inference, and monitoring

  • Deploy and support machine learning models in production environments

  • Write clean, scalable, maintainable, and well-tested Python code

  • Support monitoring, troubleshooting, and optimization of production ML systems and data pipelines

  • Collaborate cross-functionally with engineering, data science, and product teams to operationalize ML solutions

  • Improve the reliability, scalability, and performance of ML infrastructure and services

  • Contribute to tooling and processes that support the machine learning development lifecycle

  • Participate in code reviews, technical discussions, and collaborative problem solving

Required Qualifications

  • 2+ years of experience in machine learning engineering, software engineering, or related technical experience

  • Strong Python development experience

  • Experience working with machine learning frameworks such as PyTorch, TensorFlow, or scikit-learn

  • Experience deploying or supporting machine learning models in production environments

  • Experience writing clean, maintainable code and using version control tools such as Git

  • Exposure to cloud platforms such as AWS, GCP, or Azure

  • Understanding of taking machine learning models from research/development into production systems

Additional Information

  • Hybrid work environment based in Cary, NC

  • Applicants must be authorized to work in the U.S. without sponsorship

  • Competitive compensation, benefits, flexible time off, and career development opportunities