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Machine Learning Engineer Quantization Jobs in Wisconsin

Autodesk

$107K - $139K/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 ...

Autodesk

$118K - $153K/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 ...

Varsity Tutors

Machine Learning Tutor

Madison, WI · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Eliassen Group

Senior AI/ML Engineer

Madison, WI · Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning solutions on AWS. The role includes LLM orchestration, RAG pipelines, vector database integration ...

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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 Wisconsin? For Machine Learning Engineer Quantization jobs in Wisconsin, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Wisconsin look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Wisconsin are:
What cities in Wisconsin are hiring for Machine Learning Engineer Quantization jobs? Cities in Wisconsin with the most Machine Learning Engineer Quantization job openings:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Wisconsin as of June 2026, with employment types broken down into 76% Full Time, and 24% Part Time. Highlights an 87% Physical, 5% Hybrid, and 8% Remote job distribution.

Machine Learning Engineer II - Adaptive Application Algorithm

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 14 days ago

Job description

Job Description:
INNOVATE WITHOUT BOUNDARIES!
At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions on our engineering teams.
Our Engineering Team is responsible for giving life to the batteries, motors, and electronics that power solutions changing the lives of our users. Every developmental phase of these critical components happens in-house under the watch of this team. We continue to invest in electrical engineering resources to design and develop leadership in electronic capabilities; something unique within the industry. And we're pushing the limits in firmware engineering, power electronics, embedded systems, machine learning, and the use of artificial intelligence.
Behind our doors you'll be empowered every day to own it, drive it, and do what it takes to design and develop the biggest breakthroughs in the industry.
Meanwhile, you'll have the support and resources of the fastest-growing brand in the construction industry to make it happen. Year after year, our team continues to make significant breakthroughs in the industry. We're just getting started. To learn more about our story click HERE.
At Milwaukee Tool we firmly believe that our People and our Culture are the secrets to our success - so we give you unlimited access to everything you need to create disruptive new technologies and solutions on our Advanced Engineering & Technology team.
Our Team's Technology Obsession
The Adaptive Application Algorithm development team is the trusted research and knowledge bank that accelerates and delivers technological disruptive innovation to the organization. We work with cutting-edge engineering tools and spearhead the development of industry-defining technologies. Our collaborative and supportive work environment encourages out-of-the-box thinking, challenges traditional approaches, and empowers us to explore groundbreaking ideas. We are committed to staying ahead of the curve, continuously investing in research and development, and ensuring that our engineers have access to the most advanced technology.
The ideal candidate is a curious self-starter, who can drive several projects of high complexity. They are passionate about working in the ambiguous early research and development phase of engineering technologies and are eager to leverage their diverse background in Machine Learning (ML) and Artificial Intelligence (AI). They have a history of bringing fundamental technology principles to tangible applications that deliver innovation. They are hands-on, fail forward, and collaborate regularly with our cross-discipline team of various skillsets including Electrical Engineering, Cloud Architecture, Mechanical Engineering, Machine Learning Engineering, and other technical disciplines. Your extensive experience across multiple areas of Machine Learning will be invaluable in driving forward our cutting-edge projects and delivering impactful solutions.
You'll be DISRUPTIVE through these duties and responsibilities:
  • Research and introduce emergent technologies into the business which empower future product development,
  • Leverage your diverse background and deep skillset in Machine Learning to deliver technological innovation.
  • Execute applied ML for Advanced Engineering and R&D settings through proof of concepts and pilots.
  • Stay ahead of industry trends related to AI, ML, and Cloud technologies - while rapidly evaluating their fit.
  • De-risk technologies prior to business introduction by leveraging multiple approaches such as: Technology Readiness Level process, start-up engagements, and joint developments.
  • Support the engagement of external partnerships, internal partnerships, or university engagements to accelerate technology delivery.
  • Foster collaboration not only within your discipline but also with subject matter experts across the business, including mechanical, electrical and design engineers.

What TOOLS you'll bring with you:
  • Proven track record of developing, deploying, and implementing impactful AI or ML solutions connected to business objectives.
  • Effective at evaluating technology feasibility and moving through development process.
  • Demonstrated experience using fundamental ML techniques such as unsupervised, supervised, regression, dimensionality reduction, or similar.
  • Familiar with advanced Machine Learning and AI methods such as CNN's, transformers, NLP, Computer Vision, or similar.
  • Capable of developing robust MLOps pipelines to ensure efficient deployment, monitoring, and scaling of ML models.
  • Can developed in cloud, local, or edge environments leveraging associated libraries and tools.
  • Comfortable with Data Engineering, Data Collection, ETL, and data architecture principles.
  • Familiar with different types of data collection methods or hardware in an engineering lab setting.
  • Insatiably curious about emergent technologies, understanding their principles, and demonstrating their value in relevant environments.
  • Bachelor of Science degree in Machine Learning, Data Science, Electrical Engineering, Computer Science, or related field.
  • 2+ Years experience using Machine Learning Engineering skillsets in Research and Development, Advanced Engineering, or Lab environment.
  • Excellent technical communication skills and fundamental project management abilities.
  • Periodic travel may be required, up to 10%.
  • Hands on experience.

We provide these great perks and benefits:
  • Robust health, dental and vision insurance plans.
  • Generous 401 (K) savings plan.
  • Education assistance.
  • On-site wellness, fitness center, food, and coffee service.
  • And many more, check out our benefits site HERE.

Milwaukee Tool is an equal opportunity employer.

Apply