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Machine Learning Engineer Quantization Jobs in Milwaukee, WI

Milwaukee Tool

Sr Machine Learning Engineer

Milwaukee, WI · On-site

$103K - $141.40K/yr

Your role on our team As a Senior Machine Learning Engineer, you will design, develop, and deploy intelligence solutions that transform how Milwaukee Tool manufactures product - from predictive ...

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 ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI

$103K - $141.40K/yr

Work You'll Do As a Senior AI Engineer, you'll work cross-functionally with data scientists, machine learning engineers, project managers, and industry experts to develop robust AI infrastructure and ...

Purple Drive Technologies

GenAI Engineer

Waukesha, WI · On-site

The ideal candidate will have a strong background in machine learning, natural language processing ... Experience in prompt engineering, model fine-tuning, and API integration. * Solid background in ...

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Machine Learning Engineer Quantization information

See Milwaukee, WI salary details

$31K

$126.9K

$190.6K

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

As of May 29, 2026, the average yearly pay for machine learning engineer quantization in Milwaukee, WI is $126,869.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,000.00 and $152,700.00 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 Milwaukee, WI? For Machine Learning Engineer Quantization jobs in Milwaukee, WI, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Quantization jobs in Milwaukee, WI look for? The top searched job categories for Machine Learning Engineer Quantization jobs in Milwaukee, WI are:
Machine Learning Engineer Quantization jobs near you
Infographic showing various Machine Learning Engineer Quantization job openings in Milwaukee, WI as of May 2026, with employment types broken down into 1% Internship, 54% Full Time, 41% Part Time, 2% Temporary, 1% Contract, and 1% Nights. Highlights an 87% Physical, 8% Hybrid, and 5% Remote job distribution, with an average salary of $126,869 per year, or $61 per hour.

Machine Learning Engineer I

Milwaukee Tool

Brookfield, WI

Full-time

Medical, Dental, Vision, Retirement

Posted 13 days ago

Job description

Job Description:

Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.

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 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.

Your role on our team

As a Machine Learning Engineer, you will be a hands-on leader tasked with deploying machine learning models in creative ways while working with highly cross-functional teams to make power tool solutions that change the lives of our users. You will act as a technical expert in the creation and execution of these concepts into products, supporting the team through implementation, validation, and transfer to production.

This role requires excellent problem-solving skills, critical thinking, and the ability to work well under pressure in a dynamic environment. You will leverage strong technical communication skills and fundamental project management abilities to ensure clarity and alignment across teams. Additionally, you will demonstrate a strong sense of ownership for projects and tasks, with a clear understanding of how they connect to broader initiatives.

What TOOLS you'll bring with you (Required):

  • Bachelor of Science Degree in Computer Science, Computer Engineering, Electrical Engineering or other scientific or engineering discipline.
  • Completed course work or specialization in Machine Learning and/or Data Science
  • Demonstrated experience applying fundamental machine learning algorithms and techniques in a non-coursework setting (e.g. unsupervised or supervised learning, classification/regression, dimensionality reduction, model optimization)
  • Demonstrated experience with machine learning and AI methods such as CNNS, transformers, or computer vision
  • Proficient developing and debugging code in Python
  • Proficiency in Python, with extensive experience in common libraries (NumPy, pandas, scikit-learn, Matplotlib, etc.)
  • Proficiency with at least one deep learning framework (e.g. PyTorch of Tensor Flow)
  • Sold mathematical foundation in statistics, linear algebra, calculus and optimization
  • Ability to travel up to 10% of the time (domestic and international).

Other TOOLS you may have (Preferred):

  • Master's degree or PhD in Machine Learning or related field
  • At least one year of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field are preferred
  • Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
  • Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
  • Experience working with modern software development tools and version control tools

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.

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