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Machine Learning Engineer Quantization Jobs in Tennessee

Indeed

Machine Learning Engineer

Nashville, TN

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 ...

Indeed

Machine Learning Engineer III

Nashville, TN

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III, you will be a team lead. You will own one of the team's major workstreams, help drive technical direction for the ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN

$100K - $138K/yr

Your Mission, Should You Choose to Accept As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN · On-site

$100K - $138K/yr

Your Mission, Should You Choose to Accept As a Machine Learning Engineer, you will research, evaluate, and select appropriate machine Learning approaches and architectures based on the problem ...

TheIncLab

Senior Machine Learning Engineer

Nashville, TN

$100K - $138K/yr

We are looking for a Senior Machine Learning Engineer to that will focus on researching, designing, training, and evaluating machine learning models to solve complex, real-world problems. We ...

Indeed

Senior Machine Learning Engineer

Nashville, TN

$100K - $138K/yr

Comscore, Total Visits, March 2025) Day to Day As a Senior Machine Learning Engineer on our Sourcing team, you will work on developing and deploying ML and AI solutions in production. You'll be ...

Inovalon

Senior Machine Learning Engineer

Nashville, TN

$118K - $156K/yr

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

GOAT Group

Senior Machine Learning Engineer

Nashville, TN

$100K - $138K/yr

Role Overview Grailed is looking for a Senior Machine Learning Engineer to drive personalization, recommendation, and product marketplace improvement efforts. This is a high-impact role for an ...

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

Machine Learning Engineer

Upperline Health

Nashville, TN • On-site

Full-time

Posted 3 days ago

Upperline Health rating

3.0

Company rating: 3.0 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Position Overview: We are looking for a talented Machine Learning Engineer to help build and maintain machine learning pipelines that support predictive healthcare models. This role is ideal for someone with strong data engineering skills and a passion for applying machine learning to real-world healthcare challenges.
Key Responsibilities:
  • Design and implement data pipelines using SQL and Python from various data sources.
  • Synthesize large medical claims data records into useable data features.
  • Collaborate with Data Scientists to build, refine, and deploy various machine learning models in Python.
  • Learn and apply SAS as needed for dataset generation (prior experience is not required).
  • Ensure data quality, reproducibility, and performance in the pipelines.
  • Contribute to best practices for data governance and model deployment.

Qualifications:
  • 2-5+ YOE as a Machine Learning Engineer or Data Scientist with a focus on engineering data builds.
  • Proficiency in SQL/Snowflake and Python; willingness to learn SAS as needed.
  • Experience building and combining data pipelines and working with large datasets.
  • Basic understanding of healthcare claims data (e.g., Medicare claims) preferred.
  • Familiarity with machine learning workflows (e.g., scikit-learn, pandas, NumPy).
  • Strong problem-solving and communication skills, sharp critical thinking skills.
  • Comfortable with a fast-paced workstream that requires flexibility to work on multiple projects or analyses at the same time.

Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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