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Machine Learning Engineer Quantization Jobs in Georgia

Indeed

Machine Learning Engineer

Atlanta, GA

As a Machine Learning Engineer, you will prepare datasets, train and optimize models, and maintain and improve model inference services. You will learn and apply new techniques from open source ...

CNN

Machine Learning Engineer I

Atlanta, GA · On-site

CNN is a global leader in news and information, seeking a Machine Learning Engineer I to build and deploy ML systems that enhance personalization, search, recommendations, and content understanding ...

Autodesk

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$100K - $138K/yr

Position Overview As a Senior Machine Learning Engineer, you will play a key role in designing, developing, and evolving machine learning systems that support conversational AI, search, multi-agent ...

Saxon Global

Machine Learning Engineer

Atlanta, GA

We're partnering with a client to hire ML Search Engineers who are excited about building a modern, machine learning-driven search platform that powers intelligent product discovery across a large e ...

Inovalon

Senior Machine Learning Engineer

Atlanta, GA

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

Inovalon

Senior Machine Learning Engineer

Atlanta, GA · On-site +1

$117K - $155K/yr

The Senior Full-Stack Machine Learning Engineer sits within the Insights Business Unit, which serves as Inovalon's central AI and machine learning hub. This team partners with Provider, Payer, and ...

AEG Presents

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

AEG

Staff Machine Learning Engineer

Atlanta, GA · On-site

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

PrizePicks

Staff Machine Learning Engineer

Atlanta, GA · On-site +1

$220K - $280K/yr

As a Staff Machine Learning Engineer, you will lead the technical charge to scale and productionize our core machine learning capabilities. Your work will directly impact key metrics like Time-to-Bet ...

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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.

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Machine Learning Engineer Quantization jobs near you
Machine Learning Engineer

Machine Learning Engineer

Infinite Resource Solutions

Atlanta, GA

Other

Posted 7 days ago

Job description

Job Description Machine Learning Engineer Roles and Responsibilities Lead the end-to-end architecture and development of machine learning solutions. Implement machine learning algorithms into services and pipelines to be consumed at large-scale. Engineer large scale development systems using full-stack, distributed shallow and deep-learning technologies and big data technologies.

Architect and develop a highly scalable, distributed, multi-tenant set of microservices backend solutions. Be a part of a highly productive and creative engineering team What Are We Looking For in This Role. Highly Preferred: MS or PhD in Machine learning, Computer Vision, Natural Language Processing or a related field.

5+ years of experience architecting and developing AI and machine learning applications Ability to think critically, question assumptions and devise solutions to challenging technical problems. Hands-on experience with one or more of the following technologies: --Machine Learning: TensorFlow, PyTorch, Spark ML/MLib etc. --ML Technologies: NLP, Computer Vision and related technologies.

--Back end web-services: Java, Spring Boot, Python, Kubernetes, Docker - Big Data technologies: Kafka, Apache Spark, MapR, Hbase, Hive, HDFS etc. Minimum Qualifications Bachelor's Degree Relevant Experience or Degree in: Computer Science, Management Information Systems, Business or related field Typically Minimum 6 Years Relevant Exp Four-year college degree and 6 or more years, and/or a high school diploma with 8 or more years professional experience with full life cycle design and development

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