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Urgently Hiring Apple Machine Learning Engineer 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 ...

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 ...

Varsity Tutors

Machine Learning Tutor

Madison, 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 ...

TBK Bank, SSB

WI · On-site

$206.26 - $330.02/hr

We are proud to be an equal opportunity employer and we do not discriminate in recruitment, hiring ... learning. You're not just an employee -- you're part of a team shaping the future. Being part of ...

Myparadigm

WI · On-site

$140 - $190/hr

Deploy and support machine learning models and AI solutions in production, maintaining best ... Collaborate with Machine Learning Engineers, Data Scientists, Software Engineers, and ...

Paradigm

WI · On-site

$120 - $180/hr

Deploy and support machine learning models and AI solutions in production, maintaining best ... Collaborate with Machine Learning Engineers, Data Scientists, Software Engineers, and ...

Paradigm

Senior ML Ops Engineer

Middleton, WI · On-site

$123K - $170K/yr

... end-to-end machine learning lifecycle, including model training, deployment, monitoring, and ... Engineers, and Infrastructure teams to operationalize ML solutions and improve deployment ...

Jobtailor

WI · On-site

$140 - $190/hr

Partner with product, engineering, and analytics teams to translate business problems into ML ... Machine Learning Model Development * Python Programming * Data Processing Frameworks * Model ...

3M HEALTHCARE

WI · On-site

$100 - $150/hr

We're seeking a Head of Machine Learning to own and scale the ML function at Prodigal. This is the ... hiring, mentoring, and growing ML talent -- including team leads and senior engineers * Strong ...

Hispanic Alliance for Career Enhancement

WI · On-site

$107 - $261/hr

Drives the development and implementation of advanced machine learning models and algorithms to ... AI & Cloud Engineering * Design, build, and deploy production-grade LLM and GenAI applications ...

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Urgently Hiring Apple Machine Learning Engineer information

What does an Apple machine learning engineer do?

An Apple Machine Learning Engineer designs, builds, and deploys machine learning models and algorithms that enhance Apple’s products and services. They collaborate with cross-functional teams to develop innovative solutions, optimize existing machine learning systems, and ensure models run efficiently on Apple hardware and software platforms. Their work includes data analysis, model training, and performance tuning, often focusing on privacy, scalability, and user experience.

What are the key skills and qualifications needed to thrive as an Apple machine learning engineer?

To thrive as an Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning principles, often supported by a relevant degree and experience with model development. Proficiency with Python, TensorFlow or PyTorch, and familiarity with macOS/iOS development tools like Core ML are typically required. Strong problem-solving, collaboration, and communication skills help engineers to innovate and work effectively across multidisciplinary teams. These competencies are crucial for driving impactful AI solutions that enhance Apple’s products and user experiences.

What are common collaboration practices for Apple machine learning engineers working on product teams?

Apple Machine Learning Engineers typically collaborate closely with cross-functional teams, including software engineers, product managers, and data scientists. Collaboration often involves regular meetings to align on project goals, integrating machine learning models into production systems, and jointly troubleshooting issues that arise during development. Engineers are encouraged to share findings and best practices, leveraging Apple's internal tools and documentation to ensure that models are robust, scalable, and meet Apple's privacy standards. The work environment emphasizes innovation, open communication, and a high standard of quality, which means collaboration is both structured and dynamic.

What is the difference between Urgently Hiring Apple Machine Learning Engineer vs Apple Data Scientist?

AspectApple Machine Learning EngineerApple Data Scientist
Required CredentialsBachelor's or higher in CS, ML, or related; experience with ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDeveloping ML models, deploying AI solutions, coding in Python, TensorFlowAnalyzing data, creating reports, statistical modeling, data visualization
Employer & Industry UsageTech companies, AI/ML product teams, innovation labsTech companies, analytics teams, product development

While both roles involve working with data and algorithms at Apple, the Machine Learning Engineer focuses on building and deploying ML models, whereas the Data Scientist emphasizes analyzing data and deriving insights. The roles overlap but differ mainly in technical focus and daily tasks.

What cities in Wisconsin are hiring for Urgently Hiring Apple Machine Learning Engineer jobs?

Cities in Wisconsin with the most Urgently Hiring Apple Machine Learning Engineer job openings:

Urgently Hiring Apple Machine Learning Engineer jobs near you

Applied Machine Learning Engineer II - Advanced Engineering & Technology

Milwaukee Tool

Brookfield, WI • On-site

Full-time

Medical, Dental, Vision, Retirement

Re-posted 15 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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