ZipRecruiter

Log In

1

Machine Learning Engineer Quantization Jobs in Detroit, MI

Eccalon LLC

Machine Learning Engineer

Detroit, MI

The Machine Learning Engineer will be an essential member of the Research and Development Team, where we engineer large tailor-made systems to solve complex data-related problems from many domains.

JConnect Infotech

Machine learning Engineer

Warren, MI · On-site

Machine Learning Engineer Develop and deploy machine learning models that process and analyze IoT (Internet of Things) signal data. Work with large-scale sensor data from connected devices to build ...

JConnect Infotech

Machine Learning Engineer

Warren, MI · On-site

Machine Learning Engineer Location: Warren, MI / Mountain View, CA Duration: Fulltime Must Have Technical/Functional Skills: • Assist in fine-tuning VLA (Vision-Language Alignment) models for ...

Stefanini

Machine Learning Engineer

Dearborn, MI

Stefanini is looking for a Machine Learning Engineer, Dearborn, MI (Onsite) For quick apply, please reach out Saurabh Kapoor at / You will be responsible for designing, building, deploying, and ...

Indeed

Machine Learning Engineer

Detroit, MI · On-site

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

Staff Machine Learning Engineer

Detroit, MI · On-site

Comscore, Total Visits, March 2025) Day to Day As a Machine Learning Engineer III you will be a team lead on the Marketplace Efficiency - Job Reach team. Your team will be responsible for maintaining ...

Indeed

Machine Learning Engineer III

Detroit, MI · On-site

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 ...

HTC Global Services

Machine Learning Engineer

Dearborn, MI · Remote

$51.25 - $68.50/hr

We are seeking an experienced Machine Learning Engineer to design, implement, and maintain robust analytics pipeline solutions. These solutions will support the analysis, modeling, and prediction of ...

Stefanini

Machine Learning Engineer

Dearborn, MI

$105.50K - $126.60K/yr

Stefanini is looking for a Machine Learning Engineer (Dearborn, MI) For quick apply, please reach out to Adil Khan at / We are seeking a Machine Learning who can build scalable and robust ML data ...

FastTek

Machine Learning Engineer

Dearborn, MI

$105.20K - $126.30K/yr

Machine Learning Engineer #1054987 * Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions -- including Generative AI and ...

General Motors

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222.91K - $227.20K/yr

Machine Learning Frameworks, including TensorFlow and PyTorch; Mathematical Reasoning and Probability; Programming in C++ or Python; Experience with Robot Operating System (ROS), OpenCV, or PCL;

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer Quantization JobsMachine Learning Engineer Quantization Jobs in Detroit, MI

Machine Learning Engineer Quantization information

See Detroit, MI salary details

$31.2K

$127.5K

$191.6K

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

As of May 28, 2026, the average yearly pay for machine learning engineer quantization in Detroit, MI is $127,477.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $153,400.00 per year, depending on experience, location, and employer.

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

Machine Learning Engineer

Eccalon LLC

Detroit, MI

Full-time

Posted 4 days ago

Job description

Job Description

The Machine Learning Engineer will be an essential member of the Research and Development Team, where we engineer large tailor-made systems to solve complex data-related problems from many domains. At Eccalon, the projects we support often require solutions that utilize the latest and the best from Deep Learning/Machine Learning research. We support advanced projects in both data constrained and data rich settings. Qualified candidates should be driven and be able to help craft these systems as a part of our R&D team.

Responsibilities

  • Candidates are expected to be familiar with the motions of a classical Machine Learning workflow, and support the team with some of the following tasks:
    • Dataset Creation.
    • Data Exploration/Visualization.
    • Literature Review.
    • Data Wrangling.
    • Implementation and Training of Appropriate Models from Literature.
    • Characterization of Error in Models.
    • Iterative Optimization of Models.
  • On the engineering side of development, the Machine Learning Engineer will have the ability to be hands-on by:
    • Creating training and preprocessing pipelines for faster experimentation.
    • Creating algorithmic modules to interface your Models output with business requirements.
    • Integrating their code to a larger codebase.
    • Putting your model into production using AWS or GCP.

Required Qualifications

  • BS. in Computer Science, or related field.
  • 3+ years of professional Software Development experience in Python.
  • Mastery of Deep Learning fundamentals and statistics underlying Machine Learning.
  • History of software projects putting Machine Learning systems into production in any capacity.
  • History of software projects in general.
  • Deep personal interest with the complete state of the art in a subfield of Machine Learning Research.
  • Ability to work independently, and within a team.
  • Ability to communicate effectively with non-technical stakeholders and supervisors.
  • Prior project experience combining two or more of the following in a production setting:
    • Unsupervised or Semi-supervised Learning.
    • Convolutional Architectures.
    • Autoencoders.
    • Recurrent Architectures for Time-Series Applications.
    • Transformer Architectures for Natural Language Processing.
    • Generative Adversarial Architectures.

Preferred qualifications

  • MS. or PhD in Machine Learning, or related field
  • Extensive AWS or GCP experience putting scalable Machine Learning systems into production.
  • Experience working with extremely high volume / high throughput data in a data lake / data warehousing / training / production environment.
  • Has implemented cutting edge methods (e.g. a custom layer) from recent Machine Learning publications / conference proceedings and has done so in PyTorch or Tensorflow.
  • Publications in AI/ML journals or conferences.

Equal Employment Opportunity (EEO) Policy

Eccalon provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation, and training.

Eccalon logo

About Eccalon

Sourced by ZipRecruiter

We are a cross-functional collective of innovative minds that leverages technology to tackle the most challenging problems of this generation for clients, the nation, and the world. Eccalon fosters creativity, curiosity, and imagination across all departments and divisions to pioneer new ideas, products, and services. We advance innovation.​

Industry

Guided missile and space vehicle manufacturing

Company size

11 - 50 Employees

Headquarters location

Hanover, MD, US

Year founded

2017

View All Eccalon Jobs

Apply