1

Machine Learning Engineer Quantization Jobs in Mississippi

About the role Integer Technologies is seeking a Machine Learning Engineer to develop, optimize ... as quantization, pruning, distillation, and hardware acceleration (e.g., GPU/CUDA, TensorRT ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

next page

Showing results 1-20

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 Mississippi?

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

Machine Learning Engineer

Integer

Gulfport, MS • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Re-posted 7 days ago


Integer Holdings rating

7.3

Company rating: 7.3 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

322nd of 538 rated manufacturers


Job description

About the role
Integer Technologies is seeking a Machine Learning Engineer to develop, optimize, and deploy AI/ML methods that power perception and autonomy for maritime platforms. This role sits at the intersection of data science and software engineering: you will design models that turn raw maritime sensor data into reliable detection, classification, and situational awareness, and you will be responsible for integrating those models into production software that runs on the edge. Candidates must be U.S. citizens, eligible for a DoD security clearance, and capable of working across multidisciplinary teams to deliver scalable, maintainable, and mission-ready systems. Experience in maritime autonomy, sensor fusion, and distributed systems is highly desirable
What you'll do
  • Model Development: Design, train, and evaluate machine learning and deep learning models for detection, classification, segmentation, tracking, and signal analysis using maritime sensor data, with particular emphasis on sonar and other maritime sensors.
  • Sensor Data & Fusion: Develop methods to process, fuse, and exploit heterogeneous sensor streams (sonar, magnetics, IMU, etc.) to produce robust perception in challenging maritime conditions.
  • Edge Deployment: Optimize and deploy models for real-time inference on size, weight, and power constrained edge compute, applying techniques such as quantization, pruning, distillation, and hardware acceleration (e.g., GPU/CUDA, TensorRT, embedded accelerators).
  • Software Integration: Integrate ML components into production software and autonomy pipelines, ensuring reliable interfaces with sensors, middleware, and downstream systems; write well-tested, maintainable code under version control.
  • Data Pipelines & Tooling: Build pipelines and tooling for data ingestion, labeling, augmentation, and the creation of training and validation datasets that reflect real operational environments.
  • Research & Innovation: Stay current with advances in AI/ML and signal processing, and identify opportunities to extend perception and autonomy capabilities based on evolving mission requirements
  • Collaboration & Mentorship: Work across multidisciplinary teams and external partners, and contribute to a culture of technical excellence, knowledge sharing, and development best practices

Qualifications
  • Must be a U.S. Citizen with the ability to obtain and maintain a U.S. DoD Secret Clearance.
  • Bachelor's degree in relevant fields (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 7+ years of experience relevant to primary responsibilities outlined above.

OR
  • Master's degree in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field) and 5+ years of experience relevant to primary responsibilities outlined above.
  • Strong proficiency in modern programming languages (e.g., C++, Python) and common ML frameworks (e.g., PyTorch or TensorFlow), with solid software engineering fundamentals and experience using Git
  • Demonstrated experience taking ML models from prototype to integrated software
  • Solid foundation in the mathematics underpinning ML, including linear algebra, probability and statistics, and signal processing.
  • Experience working with real sensor data and an understanding of the challenges of noisy, real-world signals.
  • Excellent written and oral communication skills, and the ability to collaborate effectively across disciplines.

Additional Desired Qualifications
  • Ph.D. in relevant field (e.g., data science, computer science, computer engineering, electrical engineering, mechanical engineering, or other related field)
  • Experience developing robotic or autonomous systems, using data from various perception sensor types (sonar, magnetic, cameras, lidar, etc.) to enhance a robotic platform's perception of its surrounding environmental and potential navigational hazards
  • Experience with unmanned and autonomous systems research involving maritime autonomous systems such as uncrewed surface vessels and uncrewed underwater vessels.
  • Experience with edge processing
  • Understanding of the Navy and Department of Defense's mission, problem set, and strategy for the integration of autonomous systems.

About Integer Technologies
Integer Technologies is an applied research and product development company founded by scientists and engineers with a passion for protecting freedom with innovation. We perform R&D on next-generation systems and technologies for the Department of Defense and other U.S. Government agencies. We are hardware and software developers with experience transforming research into fieldable technology. Our core portfolio of research includes projects in power & energy systems, unmanned systems (with an emphasis on maritime systems), digital engineering, cyber security, and advanced manufacturing. Our mission is to create a safer world by translating scientific discoveries into reliable products that address urgent national security needs... at the speed of relevance.
Company Benefits
  • Integer fully covers medical, prescription, vision, and dental insurance costs for the employee and dependents. Meaning, Integer standard plan pays 100% of health insurance premiums for your entire family from a well-known national insurer, saving its employees thousands of dollars annually.
  • Relocation assistance available.
  • Base salaries which exceed local & national industry averages.
  • Year-end performance-based bonuses.
  • 401(k) with company matching that vest immediately; no funny business.
  • Paid Vacation
  • Paid Sick Leave
  • Paid Holidays

Company Perks
  • Startup culture with the stability of a large company. Integer's business plan has years of time phased contracted work, alleviating the would-be risk from a traditional small company.
  • Direct access to company leadership, prioritization of people over process, and a stellar team with a shared desire for personal and professional growth.
  • Friendly atmosphere where people enjoy not only their work and what they're creating but enjoy helping each other as well.
  • Waterfront office view!

What Integer Holdings employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom