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Machine Learning Engineer Quantization Jobs in Charlotte, NC

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

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

Software Engineer - Machine Learning

Charlotte, NC · On-site

$95K - $130K/yr

... the machine learning function at a market-leading insurance company. As one of the first data ... Leverage continuous engineering practices to deliver business value regarding effectiveness of the ...

Use imaging and machine learning tools to automate manufacturing processes * Partner with engineering, operations, and process teams to solve plant challenges * Analyze process data and apply ...

Machine Vision Engineer II

Concord, NC · On-site

$82K - $112K/yr

Use imaging and machine learning tools to automate manufacturing processes * Partner with engineering, operations, and process teams to solve plant challenges * Analyze process data and apply ...

Machine Vision Engineer II

Concord, NC · On-site

$82K - $112K/yr

Use imaging and machine learning tools to automate manufacturing processes * Partner with engineering, operations, and process teams to solve plant challenges * Analyze process data and apply ...

AI Solutions Architect

Charlotte, NC · On-site

$61.50 - $81/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Senior AI Engineer - SFL Scientific

Charlotte, NC · On-site

$102K - $140K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Overall 8 to 10 years of solid experience in the areas of data engineering machine learning data science * 4 to 6 years of strong experience with the following machine learning topics classification ...

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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 Jul 16, 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 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:
Senior Machine Learning Scientist

Senior Machine Learning Scientist

Teladoc

Concord, NC

Full-time

Posted 9 days ago


Job description

Join the team leading the next evolution of virtual care.

At Teladoc Health, you are empowered to bring your true self to work while helping millions of people live their healthiest lives.

Here you will be part of a high-performance culture where colleagues embrace challenges, drive transformative solutions, and create opportunities for growth. Together, we're transforming how better health happens.

Summary of Position

The Machine Learning effort is part of the Data Science team at Teladoc Health. 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 business-critical decision making. You will own the end-to-end machine learning lifecycle:from data and feature engineering through deployment, monitoring, experimentation, and continuous improvement(across both batch and real-time production environments).Your efforts and contributions willhavea big impactonimproving member and provider experience on the Teladoc Health platform.

This is an opportunity to apply technical rigor, scalable data processing tools, and machine learning algorithms to solve real-world business problems while engineering, deploying, measuring, and iterating machine learning solutions in production.

Essential Duties and Responsibilities

  • Build production ready time series models to predict real time KPIs as well as build optimal decision actions to manage the provider network for clinical operations business optimization

  • Propose, evaluate and interpret the results of your work for clinical, product and business decision-makers and own outcomes

  • Collaborate closely with peers and stakeholders to discover and distill requirements of problem definitions, product features and architecture to improve clinical outcomes using insights and models

  • Develop modular, well-tested, production-quality software using Python, Spark and SQL to build scalable data engineering, feature engineering, machine learning and AI pipelines following software engineering best practices.

  • Design, develop, deploy and operate scalable production machine learning and AI systems, including data transformation pipelines, feature pipelines, model training, evaluation, deployment, monitoring, retraining, and experiment tracking. Ensure robust model lifecycle management through model versioning, MLflow, automated testing, CI/CD, and production monitoring.

  • Build and optimize scalable Spark and Databricks workloads, leveraging distributed computing best practices for large-scale data processing and real-time inference.

  • Design, evaluate and integrate Large Language Models (LLMs), retrieval-augmented generation (RAG), agentic workflows, and other AI capabilities where appropriate to solve business problems.

  • Monitor production models and data pipelines for data quality, feature drift, concept drift, latency, reliability, and business performance, proactively identifying and resolving issues.

Qualifications Expected for Position

  • 8+ years of experience as a Machine Learning Scientist, Data Scientist or in a similar role within SaaS or consumer technology companies.

  • A Master's degree or higher in computer science, operations research, machine learning, information systems, engineering, or a related field

  • Demonstrated depth of experience developing clean, robust, and reusable production-quality code using Python, Spark, and SQL.

  • Extensive experience designing, building and operating production machine learning systems, including scalable software, distributed data processing, reusable feature engineering pipelines, model deployment, monitoring and continuous improvement.

  • Strong understanding of statistical modeling, machine learning algorithms, experimentation, model evaluation, forecasting, and explainability techniques, with the ability to select appropriate approaches based on business and technical constraints.

  • Excellent data analysis skills and bias to deliver, measure and iterate using experimentation and statistical analysis

  • Strong system design skills with the ability to architect scalable, maintainable, and observable machine learning solutions.

  • Ability to translate machine learning solutions into measurable business outcomes and effectively communicate technical decisions, tradeoffs, and expected value to both technical and business stakeholders.

Bonus Qualifications

  • Hands-on experience with modern data and ML platforms such as Databricks, MLflow, Delta Lake, Airflow, Terraform, or equivalent cloud-native technologies.

  • Experience building AI-powered applications using Large Language Models (LLMs), embeddings, vector databases, retrieval-augmented generation (RAG), agentic workflows, or equivalent AI technologies is highly desirable.

  • Experience applying machine learning, forecasting, optimization, or decision science techniques to large-scale operational, logistics, marketplace, or network optimization problems.

  • Experience working with healthcare data (e.g., claims or EHR) is a plus.

  • Great active listening skills to infer product/business needs and underlying context.

  • Ability to collaborate effectively with peers, and respect for member privacy.

The base salary range for this position is$150,000 - $175,000. In addition to a base salary, this position is eligible for a performance bonus and benefits (subject to eligibility requirements) listed here: Teladoc Health Benefits 2026.Total compensation is based on several factors including, but not limited to, type of position, location, education level, work experience, and certifications.This information is applicable for all full-time positions.

#LI-SS2 #LI-Remote

We follow a Flexible Vacation Policy, intended for rest, relaxation, and personal time. All time off must be approved by your manager prior to use. You will also receive 80 hours of Paid Sick, Safe, and Caregiver Leave annually. This applies to full-time positions only. If you are applying for a part-time role, your recruiter can provide additional details.

As part of our hiring process, we verify identity and credentials, conduct interviews (live or video), and screen for fraud or misrepresentation. Applicants who falsify information will be disqualified.

Teladoc Health will not sponsor or transfer employment work visas for this position. Applicants must be currently authorized to work in the United States without the need for visa sponsorship now or in the future.

Why join Teladoc Health?

  • Teladoc Health is transforming how better health happens. Learn how when you join us in pursuit of our impactful mission.

  • Chart your career path with meaningful opportunities that empower you to grow, lead, and make a difference.

  • Join a multi-faceted community that celebrates each colleague's unique perspective and is focused on continually improving, each and every day.

  • Contribute to an innovative culture where fresh ideas are valued as we increase access to care in new ways.

  • Enjoy an inclusive benefits program centered around you and your family, with tailored programs that address your unique needs.

  • Explore candidate resources with tips and tricks from Teladoc Health recruiters and learn more about our company culture by exploring #TeamTeladocHealth on LinkedIn.

As an Equal Opportunity Employer, we never have and never will discriminate against any job candidate or employee due to age, race, religion, color, ethnicity, national origin, gender, gender identity/expression, sexual orientation, membership in an employee organization, medical condition, family history, genetic information, veteran status, marital status, parental status, or pregnancy). In our innovative and inclusive workplace, we prohibit discrimination and harassment of any kind.

Teladoc Health respects your privacy and is committed to maintaining the confidentiality and security of your personal information. In furtherance of your employment relationship with Teladoc Health, we collect personal information responsibly and in accordance with applicable data privacy laws, including but not limited to, the California Consumer Privacy Act (CCPA). Personal information is defined as: Any information or set of information relating to you, including (a) all information that identifies you or could reasonably be used to identify you, and (b) all information that any applicable law treats as personal information. Teladoc Health's Notice of Privacy Practices for U.S. Employees' Personal information is available at this link.


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About Teladoc

Sourced by ZipRecruiter

Industry

Fitness and sports centers

Company size

1,001 - 5,000 Employees

Headquarters location

New York, NY, US

Year founded

2002