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Machine Learning Engineer Quantization Jobs in Detroit, MI

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Job #104271 Machine Learning Engineer Dearborn, MI (HYBRID/ONSITE) W2 CONTRACT ONLY Overview We are seeking an experienced AI Engineer to design, build, and deploy scalable AI solutions leveraging ...

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $160K/yr

As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning systems that control our mineral refining facilities. You'll start with well-scoped problems inside our ...

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 ...

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions leveraging Machine Learning, Large Language ...

Senior Machine Learning Engineer As a Senior Machine Learning Engineer within the AI Squad at Canopy and reporting to the Director of AI Engineering, you'll contribute to the development of cutting ...

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 ...

Senior Machine Learning Engineer Ascentt is building cutting-edge data analytics & AI/ML solutions for global automotive and manufacturing leaders. We turn enterprise data into real-time decisions ...

Machine Learning Engineer

Dearborn, MI

$105K - $126K/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 ...

Machine Learning Engineer

Dearborn, MI · On-site

$105K - $126K/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 ...

Machine Learning Engineer

Dearborn, MI · On-site

$105K - $126K/yr

They are seeking a Machine Learning Engineer to design and implement AI solutions, optimize systems for performance and scalability, and work with enterprise-scale data environments. Responsibilities ...

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 ...

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an experienced AI Engineer to design, develop, and deploy intelligent solutions that leverage Machine ...

Senior Machine Learning Engineer

Warren, MI · On-site +1

$222K - $227K/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;

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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 Jun 18, 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 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 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

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Posted 12 hours ago


Job description

Job Title

Machine Learning Engineer

Overview / Summary

We are seeking an experienced Machine Learning Engineer to design, implement, and maintain scalable machine learning and analytics pipeline solutions. The ideal candidate will have expertise in machine learning engineering, cloud platforms, DevSecOps practices, and data engineering technologies. This role involves building and optimizing ML infrastructure, deploying production-grade machine learning solutions, and collaborating with cross-functional teams to improve processes and business outcomes.

Key Responsibilities

  • Collaborate with business and technology stakeholders to understand current and future machine learning requirements.

  • Design and develop machine learning models and software algorithms to solve complex business problems in structured and unstructured environments.

  • Design, build, maintain, and optimize scalable machine learning pipelines, architectures, and infrastructure.

  • Apply machine learning techniques in areas such as computer vision, perception, localization, virtual reality, augmented reality, object detection, tracking, classification, and terrain mapping.

  • Deploy machine learning models and algorithms into production environments and conduct simulations for testing and validation.

  • Automate model deployment, training, and retraining using CI/CD/CT methodologies and MLOps practices.

  • Implement model management processes, including versioning and traceability across environments.

  • Develop, build, and maintain machine learning infrastructure, including data pipelines, deployment platforms, and monitoring solutions.

  • Develop and maintain tools and libraries that support machine learning development and deployment.

  • Automate machine learning workflows using DevSecOps principles and practices.

  • Collaborate with development and operations teams to improve system integration and automate ML pipelines.

  • Design, develop, and manage data flows and APIs between systems and applications.

  • Troubleshoot and resolve issues related to system communication, data flow, and data quality.

  • Collaborate with technical and non-technical stakeholders to gather requirements and ensure successful deployment of data solutions.

  • Create and maintain technical documentation for software components.

  • Ensure systems comply with evolving business needs, data governance policies, and security requirements.

  • Implement and maintain high standards of data quality and integrity.

  • Manage deliverables through project management tools.

Required Qualifications

  • Bachelor's degree in Computer Science, Information Systems, or a related field.

  • 3+ years of experience developing and deploying machine learning models in production environments.

  • 3+ years of Python programming experience.

  • 2+ years of hands-on experience with Google Cloud Platform (GCP), including services such as BigQuery, Google Cloud Storage, Cloud Composer, and/or Cloud Run.

  • Experience using version control systems such as GitHub.

  • 2+ years of experience with code quality and security scanning tools such as SonarQube, Cycode, or FOSSA.

  • 3+ years of experience with data engineering technologies such as Kubernetes, Container-as-a-Service (CaaS) platforms, OpenShift, DataProc, Spark (PySpark), or Airflow.

  • Experience with CI/CD tools and practices, including Tekton or Terraform.

  • Experience with containerization technologies such as Docker and Kubernetes.

  • Strong analytical, troubleshooting, and problem-solving skills.

  • Familiarity with cloud platforms such as AWS, Azure, or Google Cloud Platform.

  • Familiarity with Atlassian tools such as Jira and Confluence.

  • Experience working in Agile environments.

Preferred Qualifications

  • Master's degree in Computer Science, Data Science, Engineering, or a related field.

  • Experience with machine learning libraries such as TensorFlow, PyTorch, or Scikit-learn.

  • Experience with MLOps tools and platforms.

  • Experience working in fast-paced environments with multiple priorities.

  • Demonstrated commitment to continuous learning and professional development.

  • Strong problem-solving skills and passion for technical excellence and innovation.

What Makes HTC A Great Place To Build Your Future

HTC Global Services wants you to join our team. Come build new things with us and advance your career. At HTC Global, you’ll collaborate with experts, work alongside clients, and be part of high-performing teams driving success together. You’ll have long-term opportunities to grow your career and develop skills in the latest emerging technologies.

At HTC Global Services, our employees have access to a comprehensive benefits package. Benefits can include Group Health (Medical, Dental, and Vision), Paid Time Off, Paid Holidays, 401(k) matching, Group Life and Disability insurance, Professional Development opportunities, Wellness programs, and a variety of other perks.

Our success as a company is built on inclusion and diversity. HTC Global Services is committed to providing a workplace free from discrimination and harassment, where every employee is treated with dignity and respect. We celebrate differences and believe that diverse cultures, perspectives, and skills drive innovation and success. HTC is an Equal Opportunity Employer and a proud National Minority Supplier. We seek to empower each individual, fostering an environment where everyone feels valued, included, and respected.

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