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Machine Learning Engineer Quantization Jobs in North Carolina

CoVar

Machine Learning Engineer

Durham, NC · On-site

The Machine Learning Engineer will develop software and machine learning algorithms to address real-world customer issues and will have opportunities to present their work to high-level customers.

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 ...

CoVar

Machine Learning Engineer

Durham, NC · On-site

... machine learning, Bayesian models, etc. • B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field • Excellent technical communication skills • Ability to work in ...

Bespoke Labs

Machine Learning Engineer

Greenville, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Boone, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Wilmington, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Charlotte, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

High Point, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Durham, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Elon, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Greensboro, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Bespoke Labs

Machine Learning Engineer

Raleigh, NC · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

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Machine Learning Engineer Quantization information

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

Machine Learning Engineer

CoVar

Durham, NC • On-site

Full-time

Re-posted 24 days ago

Job description

Job Summary:
CoVar is a small AI/ML R&D software company in Durham, NC, that uses artificial intelligence to solve problems that matter. The Machine Learning Engineer will develop software and machine learning algorithms to address real-world customer issues and will have opportunities to present their work to high-level customers.
Responsibilities:
• help CoVar develop software and machine learning algorithms to solve real-world customer problems
• work with data, develop algorithms, evaluate results, and write the production code that goes onto real-world systems
• present your work to high-level customers in the DoD and in the industry
• publish novel work in both classified and unclassified settings
Qualifications:
Required:
• Expertise in Python (including NumPy, pandas, and other packages)
• Experience with either PyTorch or TensorFlow
• Deep understanding of machine learning fundamentals (gradient descent, cross-validation, ROC curves, confusion matrices)
• Knowledge of classical machine learning (e.g., support-vector-machines, logistic regression)
• Familiarity with computer vision algorithms like object detection networks (e.g., YOLO, CenterNet) and modern image classification techniques
• B.S., preferably M.S. or Ph.D in engineering, math, computer science, or related field
• Excellent technical communication skills
• Ability to work in Durham, NC (relocation assistance available)
• Eligibility for US security clearance (US citizenship is required)
Preferred:
• Deep knowledge of state-of-the-art in computer vision
• Department of Defense project experience
• Active US security clearance (secret or higher)
Company:
CoVar is a leader in machine learning and artificial intelligence solutions. Founded in 2011, the company is headquartered in Mclean, USA, with a team of 11-50 employees. The company is currently Early Stage.

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