ZipRecruiter

Log In

1

Machine Learning Engineer Quantization Jobs in Memphis, TN

AutoZone

Lead Data Scientist

Memphis, TN · On-site

Work with software developers and machine learning engineers to implement models into production. * Project Management : Develop and manage project plans, ensuring timely delivery and alignment with ...

micro1 AI

Domain Expert - (STEM PhD)

Memphis, TN · Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

DataAnnotation

SDLC Engineer - AI Trainer

Memphis, TN · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

DataAnnotation

QA Engineer - AI Trainer

Memphis, TN · Remote

$50 - $100/hr

As a DataAnnotation's coder, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers -- who are driving ...

micro1 AI

Engineering AI Evaluator (PhD)

Memphis, TN · Remote

$80 - $90/hr

PhD Engineer (Electrical, Mechanical, Chemical) Role Type: Contractor Location: Remote micro1 is ... Experience with or interest in AI, machine learning, or technology-driven projects (a plus, not ...

next page

Showing results 1-20

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Memphis, TN

Machine Learning Engineer Quantization information

See Memphis, TN salary details

$30.6K

$125.1K

$188K

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

As of Jul 14, 2026, the average yearly pay for machine learning engineer quantization in Memphis, TN is $125,094.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,600.00 and $150,600.00 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 Memphis, TN? For Machine Learning Engineer Quantization jobs in Memphis, TN, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Memphis, TN look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Memphis, TN are:
Machine Learning Engineer Quantization jobs near you
Sr Staff Image Data Scientist -- Time-Series & Neuroscience

Sr Staff Image Data Scientist -- Time-Series & Neuroscience

St. Jude Children's Research Hospital

Memphis, TN • On-site

Full-time

Re-posted 24 days ago

St. Jude Children's Research Hospital rating

8.4

Company rating: 8.4 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

64th of 1,020 rated hospitals

Job description

Job Summary:
St. Jude Children's Research Hospital is a leading institution focused on understanding brain development and function through innovative computational research. The Sr Staff Image Data Scientist will be responsible for architecting and developing image analysis platforms, utilizing statistical and machine learning techniques to extract insights from complex biological data.
Responsibilities:
• Develop statistical, time-series, and machine learning techniques to extract meaningful insights from complex biological data (large-scale neuroimages, light and electron microscopy, animal behavior, histopathology, etc).
• Collaborate with scientists and researchers to design experiments and optimize data acquisition protocols for effective downstream computational analysis.
• End-to-end image analysis from pre-processing and data cleaning to reporting results.
• Stay up-to-date with the latest advancements in the field of data science.
Qualifications:
Required:
• A Ph.D. or equivalent degree in mathematics, statistics, computer science, neuroscience, physics or a related field.
• Strong background in statistical analysis and machine learning algorithms.
• Proficiency in programming languages such as Python, R, MATLAB, or similar languages commonly used in scientific computing.
• Strong expertise in time-series analysis, image and signal processing, and data visualization.
• Excellent problem-solving skills and the ability to work independently as well as collaboratively in a team-oriented environment.
• Strong communication skills to effectively convey complex concepts and results to both technical and non-technical stakeholders.
• Bachelor's degree plus 8 years experience required.
• Work experience in relevant area (e.g., applied mathematics, physics, chemistry, bioinformatics, computer science, data science, computer engineering or related field).
• Demonstrated technical thought leadership in an applied computational field (e.g., computer vision, deep learning, numerical optimization, image analysis, computer game design, scientific computing, fine element analysis, scientific visualization).
• Substantial experience in image analyses, image data management, and programming (e.g., Python, R, Matlab, Java, C/C++).
• Proven performance in earlier role/comparable role.
Preferred:
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and high-performance computing environments is a plus.
• Master's degree plus six (6) years experience or PhD plus four (4) years experience preferred.
• Experience in biological/medical imaging, deep learning, image analysis platforms (e.g., ImageJ/Fiji, CellProfiler), scientific computing, scientific data visualization, scientific computer code optimization and evaluation in an HPC environment, development of algorithms, statistical methods or scientific software, working with large image data volumes, biological/medical imaging preferred.
Company:
St. Founded in 1962, the company is headquartered in Memphis, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

What St. Jude Children's Research Hospital employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply