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Machine Learning Engineer Quantization Jobs in New Orleans, LA

Pwc

AI Solutions Engineering Delivery Lead

New Orleans, LA · On-site

$98K - $129K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Deloitte

Senior Forward Deployed Engineer- AWS

New Orleans, LA · On-site

$100K - $137K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Deloitte

Lead Forward Deployed Engineer - AWS

New Orleans, LA · On-site

$98K - $129K/yr

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Pwc

CTIO AI Engineering Manager

New Orleans, LA · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Ochsner Health

AI Engineering Lead

New Orleans, LA

$98K - $129K/yr

The Lead AI Engineer leads the design, engineering, delivery, and operation of the machine-learning and conversational AI platform that powers automated patient and customer interactions. Defines AI ...

Ochsner Health

AI Engineering Lead

New Orleans, LA · On-site

$98K - $129K/yr

The Lead AI Engineer leads the design, engineering, delivery, and operation of the machine-learning and conversational AI platform that powers automated patient and customer interactions. Defines AI ...

Koitecc Solutions

AI Engineering Lead

New Orleans, LA · On-site

$200 - $250/hr

The Lead AI Engineer leads the design, engineering, delivery, and operation of the machine-learning and conversational AI platform that powers automated patient and customer interactions. Defines AI ...

New

Deloitte

Forward Deployed Engineer- AWS

New Orleans, LA · On-site

... Machine Learning Engineer (Associate - MLA-C01) or AWS Certified Data Engineer (Associate) * 1+ years of experience building reliable, maintainable, and well-documented code * Ability to travel 50 ...

Pwc

NGA AI Engineer Manager

New Orleans, LA · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Pwc

US Tech - AI Engineering Manager

New Orleans, LA · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Pwc

CTIO - AI Engineer- Senior Manager

New Orleans, LA · On-site

$91K - $321K/yr

... machine learning algorithms and predictive modeling techniques - Collaborating with clients to validate outcomes and incorporate feedback into data solutions - Directing teams through complex ...

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Showing results 21-40

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in New Orleans, LA

Machine Learning Engineer Quantization information

See New Orleans, LA salary details

$30.3K

$123.7K

$185.8K

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

As of Sep 9, 2026, the average yearly pay for machine learning engineer quantization in New Orleans, LA is $123,665.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,500.00 and $148,900.00 per year, depending on experience, location, and employer.

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 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 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 New Orleans, LA?

For Machine Learning Engineer Quantization jobs in New Orleans, LA, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Quantization jobs in New Orleans, LA look for?

The top searched job categories for Machine Learning Engineer Quantization jobs in New Orleans, LA are:

Machine Learning Engineer Quantization jobs near you

Industrial AI Robotics Engineer

Kenner, LA

OneSource Professional Search
Recruiting and Staffing Services • 11 - 50 employees
Learn more about OneSource Professional Searchexternal

Full-time

Re-posted 21 days ago

Job description

We're supporting a well-established industrial manufacturing company with a search for an Industrial AI Vision Robotics Engineer to help develop next-generation AI-powered vision systems and robotic automation solutions. This is an opportunity to work on cutting-edge applications that combine artificial intelligence, computer vision, robotics, and industrial automation to improve manufacturing processes through advanced machine learning and edge computing technologies.

What You'll Do

  • Develop AI-powered computer vision systems for object identification, classification, tracking, and robotic automation.
  • Design, train, and optimize machine learning models for real-world industrial applications.
  • Deploy edge AI solutions using NVIDIA hardware platforms, including Jetson devices and CUDA-enabled GPUs.
  • Integrate vision systems with robotic arms, conveyors, sensors, and automated equipment.
  • Support image acquisition, camera calibration, dataset development, testing, validation, and performance optimization.
  • Collaborate with mechanical, electrical, software, and manufacturing teams to bring new automation technologies from concept through implementation.
  • Troubleshoot and improve AI and robotic systems to maximize reliability, accuracy, and throughput.
  • Stay current with emerging technologies in AI, robotics, computer vision, and industrial automation.

Qualifications

  • Bachelor's degree in Robotics Engineering, Computer Engineering, Electrical Engineering, Computer Science, Mechatronics, or a related technical field.
  • 3–5 years of experience in AI, robotics, machine vision, automation, or a related engineering discipline.
  • Experience with machine learning frameworks (such as ROS/ROS2) and programming in Python and/or C++.
  • Hands-on experience with NVIDIA Jetson, CUDA, TensorRT, or similar AI acceleration technologies.
  • Strong analytical, troubleshooting, and problem-solving skills.
  • Ability to work collaboratively in a fast-paced engineering environment.

Why Join?

  • Opportunity to develop innovative AI and robotic automation technologies with real-world impact.
  • Work alongside multidisciplinary engineering teams on new product development and emerging technologies.
  • Stable, growing manufacturing organization with a strong commitment to engineering innovation.

Employment visa sponsorship is unavailable for this position. Applicants requiring employment visa sponsorship now or in the future (e.g., F-1 STEM OPT, H-1B, TN, J1 etc.) will not be considered.