ZipRecruiter

Log In

1

Machine Learning Engineer Quantization Jobs in Charlotte, NC

The Hartford

Senior AI Machine Learning Engineer

Charlotte, NC · On-site

$119K - $157K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Euclid Innovations

ML Engineer

Charlotte, NC · On-site

Euclid Innovations is seeking a skilled and experienced Machine Learning Engineer to design and implement solutions for extracting, processing, and storing information from large-scale document ...

Autodesk

Senior Machine Learning Test Engineer

Concord, NC · On-site +1

$102K - $133K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Xsolla

Principal / Staff Data Scientist

Concord, NC · Remote

ABOUT YOU We are looking for an accomplished Principal Machine Learning Engineer to join our global ... Model serving and inference optimization (vLLM-class serving, quantization). Nice-to-Have:

New

Teladoc

Senior Machine Learning Scientist

Concord, NC · On-site

In this role, you will partner with Product, Engineering, Clinical,Operations, Marketing and Data Engineering to design, build, deploy, andoperatescalable machine learning and AI systems that power ...

Varsity Tutors

Machine Learning Tutor

Charlotte, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Matthews, NC · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Pwc

AI Engineer

Charlotte, NC · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ... using quantization, inference acceleration, and model-routing techniques - Designing agent ...

previous pagenext page

Showing results 21-40

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

Machine Learning Engineer Quantization information

See Charlotte, NC salary details

$30.8K

$125.8K

$189K

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

As of Aug 6, 2026, the average yearly pay for machine learning engineer quantization in Charlotte, NC is $125,771.00, according to ZipRecruiter salary data. Most workers in this role earn between $99,100.00 and $151,400.00 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 Charlotte, NC? For Machine Learning Engineer Quantization jobs in Charlotte, NC, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Charlotte, NC look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Charlotte, NC are:
What cities near Charlotte, NC are hiring for Machine Learning Engineer Quantization jobs? Cities near Charlotte, NC with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you

Data Scientist / Machine Learning Engineer (Generative AI Focus)

Strategic Staffing Solutions

Charlotte, NC • On-site, Remote

Other

Re-posted 27 days ago

Job description

Job Description STRATEGIC STAFFING SOLUTIONS HAS AN OPENING. This is a Contract Opportunity with our company that MUST be worked on a W2 Only. No C2C eligibility for this position.

Visa Sponsorship is Available. The details are below. "Beware of scams.

S3 never asks for money during its onboarding process." Job Title: Data Scientist / Machine Learning Engineer (Generative AI Focus) Contract Length: 12+ Months Hybrid schedule 3 days per week onsite/ 2 remote Location: Charlotte, NC/ Irving, TX/ Boston, MA Ref# 246769 We are seeking a highly motivated Data Scientist / Machine Learning Engineer to build advanced analytics and Generative AI (Gen AI) solutions across multiple business functions. This role combines strong data analysis capabilities with machine learning and emerging Gen AI techniques to drive business insights, automation, and innovation. The ideal candidate is hands-on, analytical, and comfortable owning the full lifecycle of data science solutions-from problem definition through model development and deployment-while collaborating closely with engineering and business stakeholders

Key Responsibilities Perform in-depth data analysis and exploration using SQL and statistical techniques to uncover patterns, solve business problems, and support data-driven decision-making. Work with large, complex datasets while ensuring data quality, integrity, and usability. Design, develop, and implement scalable solutions using Python or Java.

Utilize data science and machine learning libraries such as NumPy, SciPy, Matplotlib, and Scikit-learn. Build reusable pipelines for data processing, feature engineering, and model evaluation. Develop and evaluate machine learning models, including tree-based and ensemble algorithms such as Random Forest and XGBoost.

Assess model performance, tune hyperparameters, and ensure models meet business and technical requirements. Apply AI-assisted techniques to enhance productivity and insights. Craft effective prompts using Gemini or similar generative AI models to support data exploration, feature generation, analysis, and summarization.

Communicate insights through visualizations, reports, and presentations. Translate complex technical findings into actionable business recommendations. Partner closely with engineering teams for implementation and business stakeholders to ensure alignment with strategic objectives.

Required Qualifications Strong SQL and data analysis skills. Experience working with structured and semi-structured datasets. Proficiency in Python or Java for data science, machine learning, and analytical workloads.

Hands-on experience with machine learning frameworks and model development. Experience building, training, and evaluating predictive models in production or near-production environments. Ability to work independently and own initiatives end-to-end, from problem definition and requirements gathering through solution delivery and validation.

Experience using generative AI models to augment analytical workflows. Familiarity with prompt engineering. Experience leveraging large language models (LLMs) for automation and analytical tasks.

Experience integrating Gen AI capabilities into analytical processes. Generative AI Focus Develop and deploy Gen AI solutions that enhance productivity, automate workflows, and generate AI-driven business insights. Apply foundational knowledge of Gen AI concepts, tools, and use cases.

Experience with large language models (LLMs), prompt engineering, or AI-assisted analytics. Strong interest in emerging AI technologies and a willingness to continuously learn and apply new Gen AI innovations. Preferred Qualifications Experience working in financial services, banking, or capital markets environments.

Experience in data-driven or risk-focused domains. Familiarity with cloud platforms. Experience with data engineering pipelines.

Familiarity with model deployment frameworks. Exposure to big data technologies. Experience with distributed computing environments.

Exposure to real-time analytics environments. Ideal Candidate Profile Self-driven data professional with strong analytical and problem-solving skills. Combines practical machine learning expertise with emerging AI capabilities.

Comfortable navigating ambiguous problems and translating business needs into technical solutions. Capable of delivering measurable business outcomes. Strong communication skills with both technical and non-technical stakeholders.

Passionate about applying traditional machine learning and modern Generative AI techniques to solve complex business challenges.

Apply