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Machine Learning Engineer Ts Sci Jobs in Milwaukee, WI

KOHLS

Senior MLOps Engineer (Remote)

Menomonee Falls, WI · On-site

$104K - $144K/yr

Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including ... developing reusable frameworks and standardized solutions to streamline model implementation

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $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 ...

Generac

Principal Data & AI Architect

Waukesha, WI · On-site

Relevant certifications such as AWS Certified Machine Learning - Specialty, Google Professional Machine Learning Engineer, or Microsoft Certified: Azure AI Engineer Associate. Work Experience

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI

$103K - $141K/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 ...

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All JobsMachine Learning Engineer Ts Sci JobsMachine Learning Engineer Ts Sci Jobs in Milwaukee, WI

Machine Learning Engineer Ts Sci information

See Milwaukee, WI salary details

$31K

$126.9K

$190.6K

How much do machine learning engineer ts sci jobs pay per year?

As of Aug 23, 2026, the average yearly pay for machine learning engineer ts sci 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 is a machine learning engineer TS SCI?

Machine Learning Engineer TS/SCI positions are specialized roles where engineers design, develop, and implement machine learning models and systems, often for government or defense projects that require a Top Secret/Sensitive Compartmented Information (TS/SCI) security clearance. These professionals work on advanced AI algorithms, data processing, and secure software, ensuring that sensitive information is protected throughout the process. They collaborate with data scientists, software developers, and security experts to solve complex problems using data-driven approaches while adhering to strict security protocols.

What are the key skills and qualifications needed to thrive as a machine learning engineer TS SCI?

To thrive as a Machine Learning Engineer with TS/SCI clearance, you need strong skills in machine learning algorithms, programming (Python, R), data analysis, and a relevant degree in computer science or a related field, along with active TS/SCI security clearance. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (AWS, Azure), and knowledge of secure data handling are commonly required. Excellent problem-solving, teamwork, and clear communication are vital soft skills for collaborating on complex, sensitive projects. These skills ensure effective development of secure, high-impact AI solutions in environments where data protection and analytical precision are critical.

What are some common challenges faced by machine learning engineers with TS SCI in day-to-day work?

Machine Learning Engineers with TS/SCI clearance often encounter unique challenges, such as working with highly sensitive data in secure environments, which can limit access to certain tools or cloud resources. Collaboration is often restricted to cleared team members, and sharing findings externally is not permitted. Additionally, projects may have ambiguous requirements due to their classified nature, requiring strong problem-solving skills and adaptability. However, these roles offer the chance to work on impactful projects with significant national security implications, providing both technical and professional growth.

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

AspectMachine Learning Engineer Ts SciData Scientist
Required CredentialsBachelor's or Master's in CS, Data Science, or related fields; certifications in ML or AIBachelor's or Master's in Statistics, Data Science, or related fields; certifications in data analysis or visualization
Work EnvironmentDevelops and deploys ML models, often in production environmentsAnalyzes data, builds models, and provides insights for decision-making
Employer & Industry UsageTech companies, AI firms, R&D departmentsFinance, healthcare, marketing, and tech sectors

While both roles require strong analytical skills and knowledge of machine learning, Machine Learning Engineer Ts Sci focuses on developing and deploying scalable ML models, whereas Data Scientists primarily analyze data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

What are popular job titles related to Machine Learning Engineer Ts Sci jobs in Milwaukee, WI?

For Machine Learning Engineer Ts Sci jobs in Milwaukee, WI, the most frequently searched job titles are:

What job categories do people searching Machine Learning Engineer Ts Sci jobs in Milwaukee, WI look for?

The top searched job categories for Machine Learning Engineer Ts Sci jobs in Milwaukee, WI are:

Machine Learning Engineer Ts Sci jobs near you

Machine Learning Engineer II

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Re-posted 6 days ago

Job description

Job Summary:
Milwaukee Tool is a company that invests in engineering resources to design and develop leadership in electronic capabilities. As a Machine Learning Engineer II, you will be responsible for creating and validating machine learning models while collaborating with cross-functional teams to enhance power tool solutions.
Responsibilities:
• create, develop, and validate machine learning models
• work with highly cross-functional teams to make power tool solutions
• innovate and explore new machine learning solutions to deploy into Milwaukee products
• demonstrate excellent problem-solving skills
• exhibit critical thinking and thrive under pressure in a dynamic environment
• show strong technical communication skills
• exhibit fundamental project management abilities
• maintain a proactive sense of ownership for projects and tasks
• understand how projects connect to broader initiatives
Qualifications:
Required:
• Applicants must be authorized to work in the U.S.; Sponsorship is not available for this position at this time.
• 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
• 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
• 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)
• Solid mathematical foundation in statistics, linear algebra, calculus and optimization
• Experience working with modern software development tools and version control tools
• Excellent problem-solving skills, critical thinking, and ability to work well under pressure in a dynamic environment.
• Excellent technical communication skills and fundamental project management abilities
• Demonstrated strong sense of ownership of a project or tasks and understanding of relationships to other tasks/projects
• Ability to travel up to 10% of the time (domestic and international).
Preferred:
• Master’s degree or PhD in Machine Learning or related field is preferred
• At least three years of hands-on experience applying machine learning principles and algorithms involving embedded systems, edge computing, signal processing or a related field (an advanced degree may count toward some experience)
• Experience with time series modelling, especially with related domains such as NLP, SLAM, forecasting, or audio/video processing
• Proven track record of developing, deploying and implementing AI or ML solutions connected to business objectives
• Proficient developing and debugging code in an embedded environment in a programming language such as C or C++
• Working knowledge of various sensor technologies (e.g. IMU, thermistors, magnetic and optical) and interfacing to microcontrollers
• Working knowledge of embedded systems architecture (HW & SW), microcontroller design and operation
• Experience with different types of data collection methods, understanding their principles and demonstrating their value in relevant environments
• Experience developing and deploying machine learning algorithms to edge environments
• Demonstrated ability to develop robust MLOps pipelines and ensure efficient deployment, monitoring and scaling of ML models
Company:
Milwaukee Tool manufactures electric power tools and accessories. It is a sub-organization of Techtronic Industries. Founded in 1924, the company is headquartered in Brookfield, USA, with a team of 5001-10000 employees. The company is currently Late Stage.

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