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Machine Learning Engineer Quantization Jobs in Detroit, MI

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103K - $134K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Showing results 41-60

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 Aug 17, 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 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 Detroit, MI?

For Machine Learning Engineer Quantization jobs in Detroit, MI, the most frequently searched job titles 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:

Senior Machine Learning Engineer (Computer Vision & AI)

Faurecia

Auburn Hills, MI

$115K - $152K/yr

Full-time

Re-posted 27 days ago


Faurecia rating

5.9

Company rating: 5.9 out of 10

Based on 18 frontline employees who took The Breakroom Quiz


Job description

Forvia, a sustainable mobility technology leader We pioneer technology for mobility experience that matter to people. Your mission, roles and responsibilities Role Summary As a Senior Machine Learning Engineer, you will play a key role in developing and deploying advanced AI solutions that drive innovation across our automotive products and manufacturing processes. This role is focused on applied machine learning, with an emphasis on computer vision, predictive analytics, and scalable model deployment.

You will partner with cross-functional teams across engineering, manufacturing, and R&D to design, build, and productionize machine learning models that deliver measurable business impact. This is a hands-on role requiring strong technical depth, ownership of model lifecycle, and the ability to operate effectively in a fast-paced, evolving environment. Key Responsibilities Design, develop, and deploy machine learning models with a focus on computer vision, predictive maintenance, and anomaly detection Build and maintain end-to-end ML pipelines, including data preprocessing, model training, evaluation, and deployment Collaborate with engineering, manufacturing, and business stakeholders to translate real-world problems into scalable AI solutions Optimize model performance and scalability using GPU acceleration and parallel computing frameworks Leverage Python and deep learning frameworks (PyTorch, TensorFlow) to implement production-ready solutions Partner with data and software engineering teams to integrate models into production systems and workflows Contribute to AI innovation initiatives, including exploration of generative AI use cases in design and engineering contexts Ensure best practices in model reproducibility, documentation, and performance monitoring Stay current with advancements in machine learning and apply relevant techniques to improve existing capabilities Your profile and competencies to succeed Your Profile & Competencies Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related field 5+ years (preferably 7+) of hands-on experience in machine learning or applied AI roles Strong expertise in machine learning and deep learning, with practical experience in computer vision applications Proficiency in Python and modern ML frameworks such as PyTorch or TensorFlow Experience building and deploying models in production environments Familiarity with GPU acceleration (CUDA or similar frameworks) and performance optimization techniques Experience with ML pipelines, model lifecycle management, and scalable system design Ability to work effectively in matrixed, cross-functional environments Strong problem-solving and analytical skills, with the ability to translate complex data into actionable insights Effective communicator, able to explain technical concepts to non-technical stakeholders Experience in automotive, manufacturing, or industrial environments is a strong plus Familiarity with cloud platforms (e.g., Azure) and Agile development practices is preferred What we can do for you At Forvia, you will find an engaging and dynamic environment where you can contribute to the development of sustainable mobility leading technologies

We are the seventh-largest global automotive supplier, employing more than 157,000 people in more than 40 countries which makes a lot of opportunity for career development. We welcome energetic and agile people who can thrive in a fast-changing environment. People who share our strong values.

Team players with a collaborative mindset and a passion to deliver high standards for our clients. Lifelong learners. High performers.

Globally minded people who aspire to work in a transforming industry, where excellence, speed, and quality count. We cultivate a learning environment, dedicating tools and resources to ensure we remain at the forefront of mobility. Our people enjoy an average of more than 22 hours of online and in-person training within FORVIA University (five campuses around the world) We offer a multicultural environment that values diversity and international collaboration.

We believe that diversity is a strength. To create an inclusive culture where all forms of diversity create real value for the company, we have adopted gender diversity targets and inclusion action plans. Achieving CO2 Net Zero as a pioneer of the automotive industry is a priority: In June 2022, Forvia became the first global automotive group to be certified with the new SBTI Net-Zero Standard (the most ambitious standard of SBTi), aligned with the ambition of the 2015 Paris Agreement of limiting global warming to 1.5C

Three principles guide our action:use less, use betteranduse longer, with a focus on recyclability and circular economy. Why join us FORVIA is an automotive technology group at the heart of smarter and more sustainable mobility. We bring together expertise in electronics, clean mobility, lighting, interiors, seating, and lifecycle solutions to drive change in the automotive industry.

With a history stretching back more than a century, we are the 7th largest global automotive supplier, employing more than 157,000 people in 43 countries. You'll find our technology in around 1 out of 2 vehicles produced anywhere in the world. In June 2022, we became the 1st global automotive group to be certified with the SBTI Net-Zero Standard.

We have committed to reach CO2 Net Zero by no later than 2045. As technological innovation and the need for sustainability transform the automotive industry, we are ideally positioned to deliver solutions that will enhance the lives of road-users everywhere.


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