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Machine Learning Engineer Opt Jobs in Wisconsin (NOW HIRING)

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 ...

$225K - $260K/yr

Master's or PhD in Computer Science, Robotics, Electrical Engineering, Machine Learning, or a closely related technical discipline. * Minimum of 5 years of professional experience developing ...

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Machine Learning Engineer Opt information

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models into production environments. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, reliable systems that organizations can use to make predictions or automate tasks. Their responsibilities include data preprocessing, choosing appropriate algorithms, model training, and ensuring the model's performance in real-world applications. Machine Learning Engineers often collaborate with data scientists, data engineers, and product teams to deliver intelligent solutions.

What is the difference between Machine Learning Engineer Opt vs Data Scientist?

AspectMachine Learning Engineer OptData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; certifications in ML toolsBachelor's or Master's in CS, Statistics, or related fields; data analysis certifications
Work EnvironmentDevelops, tests, and deploys ML models in production systemsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI startups, e-commerce, financeResearch institutions, tech firms, consulting, finance
Common Search & ComparisonOften compared for technical skills and deployment focusCompared for data analysis and business insights

Machine Learning Engineers Opt focus on deploying scalable ML models in production environments, while Data Scientists primarily analyze data and develop models for insights. Both roles require strong technical skills, but their core responsibilities differ in application and deployment.

Is a machine learning engineer still in demand?

Yes, machine learning engineers are in high demand due to the growing adoption of AI and data-driven solutions across industries. They are sought after for their skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, and cloud platforms, making this a strong career choice for those with relevant expertise.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances because they develop and refine AI models, requiring specialized skills in programming, data analysis, and domain knowledge. Jobs that involve complex problem-solving, creativity, and emotional intelligence, such as healthcare professionals, educators, and skilled tradespeople, are also expected to persist despite AI automation. Continuous learning and adapting to new tools and technologies will be essential for job security across many fields.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science, engineering, or a related field. Familiarity with machine learning frameworks (such as TensorFlow, PyTorch), data processing tools, and cloud platforms, along with relevant certifications, is highly valuable. Strong problem-solving ability, collaboration, and effective communication are standout soft skills in this role. These skills and qualities ensure the successful development, deployment, and integration of machine learning solutions that drive business value.

What is a $900,000 AI job?

A $900,000 AI-related job typically refers to high-level roles such as senior machine learning engineers, AI research directors, or chief AI officers, often in large tech companies or specialized firms. These positions usually require advanced skills in machine learning, deep learning, and data science, along with extensive experience and leadership responsibilities.

What are some common challenges Machine Learning Engineers face when deploying models to production environments?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, handling data drift, and integrating models seamlessly with existing systems when deploying to production. Monitoring model performance in real time and retraining models as new data becomes available are also critical tasks. Collaboration with data engineers and DevOps teams is essential to address infrastructure and deployment hurdles while maintaining model accuracy and reliability.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-paying industries such as finance or tech, can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially at large tech companies or startups with significant funding.

Machine Learning Engineer I

Milwaukee Tool

Brookfield, WI

Other

Medical, Dental, Vision, Retirement

Posted 4 days ago


Job description

Machine Learning Engineer

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 or 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.