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Junior Machine Learning Engineer New Grad Jobs in Milwaukee, WI

Varsity Tutors

Machine Learning Tutor

Milwaukee, WI · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West ...

Deloitte

Senior AI Engineer - SFL Scientific

Milwaukee, WI · On-site

$103K - $141K/yr

Work with clients to design, develop, and deploy new architectures to support machine learning ... Mentor, motivate, and coach junior members on technical best practices and inspire professional ...

Symbotic

New Grad- Integration Specialist

Kenosha, WI · On-site

$82K - $113K/yr

New Grad- Integration Specialist We want to learn from you! Our teams at Symbotic value the early ... What we need The Integration Specialist role is to startup, commission, test PLC (Programmable ...

Symbotic

New Grad- Integration Specialist

Racine, WI · On-site

$82K - $113K/yr

New Grad- Integration Specialist We want to learn from you! Our teams at Symbotic value the early ... What we need The Integration Specialist role is to startup, commission, test PLC (Programmable ...

Symbotic

New Grad- Integration Specialist

Milwaukee, WI · On-site

$82K - $113K/yr

New Grad- Integration Specialist We want to learn from you! Our teams at Symbotic value the early ... What we need The Integration Specialist role is to startup, commission, test PLC (Programmable ...

Ultimus Fund Solutions

Senior AI Engineer

Milwaukee, WI · On-site

$103K - $141K/yr

Architect and scale machine learning pipelines to support automated workflows across Fund ... Mentor junior engineering staff and advise the Managing Director on technical priorities and secure ...

Generac

Principal Data & AI Architect

Waukesha, WI

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

New

Pwc

CTIO AI Engineering Manager

Milwaukee, WI

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

Pwc

AI Engineer

Milwaukee, WI · On-site

$50K - $112K/yr

... new technologies and methodologies in AI engineering What You Must Have - At least a Bachelor ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

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Junior Machine Learning Engineer New Grad information

See Milwaukee, WI salary details

$33K

$70.7K

$107.9K

How much do junior machine learning engineer new grad jobs pay per year?

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer new grad in Milwaukee, WI is $70,740.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,800.00 and $78,800.00 per year, depending on experience, location, and employer.

What cities near Milwaukee, WI are hiring for Junior Machine Learning Engineer New Grad jobs?

Cities near Milwaukee, WI with the most Junior Machine Learning Engineer New Grad job openings:

Junior Machine Learning Engineer New Grad jobs near you

Applied Machine Learning Engineer II - Advanced Engineering & Technology

Milwaukee Tool

Brookfield, WI • On-site

Other

Medical, Dental, Vision, Retirement

Re-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.
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.
Your Role on the Team:
As a member of the Advanced Engineering and Technology (AET) Team in the Power Tool Accessories business unit you will utilize your expertise in machine learning to solve problems where no established solution exists and deliver first-of-its-kind technologies at Milwaukee Tool. You will research, prototype, and deliver ML-driven capabilities that accelerate how we design and develop products. You will take ideas from conceptual whiteboard architectures through functional prototypes and hand-off integrations, delivering technology innovation to product and production engineering teams. This role is an individual contributor position focused on applied execution and technology demonstration, working under shared technical direction.
Why This Role is Different:
  • Full-Stack ML in a Physical Domain: Work across the ML stack, from machine and sensor-level data through model deployment on edge hardware or cloud infrastructure.
  • R&D Engineering First: Apply ML across Technology Readiness Levels (TRL 1-7), bringing technology innovation to life beyond model tuning. Domain knowledge in materials, mechanics, signals, or physics is central to this role.
  • Flexible Tools: Select and use frameworks and libraries best suited to the problem, without being constrained to a single ecosystem.
  • Real Impact: Deliver ML-driven capabilities that shorten product development cycles and unlock new engineering possibilities at Milwaukee Tool.

What You'll Do:
  • Research and evaluate emerging AI and ML technologies, advancing them through the Technology Readiness Level (TRL) process from concept through technology integration.
  • Frame engineering problems as ML problems by assessing ML value versus physics-based or analytical approaches and defining practical success criteria.
  • Design, train, evaluate, and deploy ML models to solve applied science and engineering problems that expand product development capabilities.
  • Build end-to-end ML workflows spanning data acquisition, feature engineering, model development, validation, and deployment (PyTorch, TensorFlow, CUDA, Azure ML).
  • Deploy ML enabled systems on edge hardware and cloud infrastructure to support engineering decisions.
  • Prepare technology transfer packages by documenting architecture decisions, known limitations, data requirements, and deployment specifications to enable technology adoption.
  • Collaborate with cross-functional teams to deliver ML solutions aligned with engineering needs.
  • Identify and assess emerging technologies via literature, universities, conferences, and vendor engagement.

What You'll Bring:
Required
  • BS in Mechanical Engineering, Electrical Engineering, Materials Science, Physics, Computer Science, Data Science, or related engineering discipline, with advanced coursework or experience in Machine Learning.
  • +3 or more years of experience applying ML to physical-world engineering or scientific problems (materials, mechanical systems, manufacturing, sensor systems, chemical processes, or similar).
  • Demonstrated experience designing, training, evaluating, and deploying ML models on real-world problems.
  • Strong working knowledge of Python and the scientific computing ecosystem (NumPy, SciPy, Pandas, scikit-learn), with working knowledge of SQL.
  • Hands-on experience with at least one deep learning framework (PyTorch or TensorFlow) and familiarity with cloud ML platforms (Azure ML, AWS SageMaker, or equivalent).
  • Strong mathematical foundations in linear algebra, probability, statistics, and optimization, with the ability to reason about loss functions, convergence behavior, and model assumptions.
  • Demonstrated ability to formulate ambiguous engineering or scientific problems into well-defined ML problems with clear objectives and evaluation criteria.
  • Curiosity-driven approach to learning new technologies and methods, with emphasis on applying machine learning to real-world scientific and engineering challenges.
  • Ability to work across a diverse range of data types.
  • Hands-on approach to collaboration and evaluation of technologies.
  • Ability to thrive in an ambiguous and fast-paced environment, where problem definitions evolve.
  • Ability to travel 10% of the time (domestic and international).

Preferred
  • Master's Degree or PhD in relevant field.
  • Familiarity with physics-informed ML approaches, embedding physical constraints in model architecture, or surrogate modeling for simulation acceleration.
  • Experience with computer vision for engineering applications.
  • Exposure to edge deployment: model optimization containerized deployment to industrial hardware.
  • Experience with design of experiments (DOE), uncertainty quantification, or Bayesian optimization.
  • Familiarity with version control, experiment tracking, and reproducible research practices

Working Environment
  • In-Person, Office Environment, R&D Engineering Lab

Our 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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