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Junior Machine Learning Engineer Jobs in Whitewater, WI

You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform data from diverse sources into trusted, high-quality, and reusable ...

You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform data from diverse sources into trusted, high-quality, and reusable ...

Senior Engine Code Engineer

Waukesha, WI · On-site

$104K - $143K/yr

The Senior Engine Code Engineer plays an important role in advancing the design and performance of ... Familiarity with machine learning and predictive analytics techniques applied to engine performance ...

Senior Platform & Analytics Analyst

Waukesha, WI · On-site

$86K - $108K/yr

Collaboration with cross-functional teams in manufacturing, Engineering ops, Marketing & sales ... Additional duties include leading advanced analytics projects with machine learning and AI for ...

... machine learning, and the use of artificial intelligence. Behind our doors you'll be empowered ... and coaching junior Engineers. * Work with component suppliers and manufacturers for proper ...

... machine learning, and the use of artificial intelligence. Behind our doors you'll be empowered ... Role model Milwaukee Tool's culture while providing technical guidance and mentorship to junior ...

Junior Sales Engineer

Franklin, WI · On-site

$60K - $75K/yr

Without the people in our organization we would sell nothing but machines and wouldn't be able to ... Performs other duties and responsibilities as requested Requirements: * BS Degree in Engineering ...

Without the people in our organization we would sell nothing but machines and wouldn't be able to ... Performs other duties and responsibilities as requested Requirements: * BS Degree in Engineering ...

Sr Electrical Engineer

Brookfield, WI · On-site

$100K - $131K/yr

... machine learning, and the use of artificial intelligence. Behind our doors you'll be empowered ... Serve as a role model Milwaukee Tool's culture while mentoring, guiding, and coaching junior ...

Manufacturing Engineer

Waukesha, WI · On-site

$73K - $94K/yr

Work with engineering department to improve designs for manufacturability. Help to study ... automation (RPA), machine learning, artificial intelligence, or industrial control systems

Showing results 21-40

Junior Machine Learning Engineer information

See Whitewater, WI salary details

$33K

$70.7K

$107.9K

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

As of Aug 20, 2026, the average yearly pay for junior machine learning engineer in Whitewater, WI is $70,746.00, 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 does a junior machine learning engineer do?

As a junior machine learning engineer, you work in AI, performing research with algorithms and data modeling techniques. Machine learning involves using large collections of data to create systems that are capable of making predictions, and in this field, your duties and responsibilities revolve around using advanced mathematics to design applications for use in everything from stock trading to sports betting. Some machine learning efforts involve images, and this branch of the field is known as computer vision, while other techniques which focus on text are called natural language processing (NLP). Given these divisions, titles in machine learning include computer vision engineer, NLP scientist, or simply research scientist.

What kinds of projects and responsibilities can a junior machine learning engineer expect in their first year on the job?

As a Junior Machine Learning Engineer, you’ll typically work on tasks such as data preprocessing, building and testing simple models, and supporting more senior engineers in deploying machine learning solutions. Your responsibilities may also include cleaning datasets, implementing basic algorithms, and running experiments to evaluate model performance. You’ll often collaborate closely with data scientists, software engineers, and product teams to understand project goals and learn best practices. The role provides excellent opportunities to develop your technical skills, gain exposure to various stages of the ML pipeline, and gradually take on more complex projects as you grow.

What are the key skills and qualifications needed to thrive as a junior machine learning engineer, and why are they important?

To succeed as a Junior Machine Learning Engineer, you need a solid grasp of programming (especially Python), foundational knowledge of algorithms and statistics, and a relevant degree in computer science, mathematics, or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch and tools like scikit-learn, as well as experience with version control systems like Git, are typically required. Strong problem-solving abilities, attention to detail, and a willingness to learn from feedback are valuable soft skills that help you adapt and grow in the field. These skills ensure you can effectively develop, test, and improve machine learning models while collaborating with more experienced engineers and contributing to team projects.

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

AspectJunior Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; some experience with ML frameworksBachelor's or higher in CS, Statistics, or related; often advanced certifications
Work EnvironmentDeveloping and deploying ML models, coding, testingData analysis, statistical modeling, interpreting data insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, tech, consulting
Search & Comparison IntentYesYes

While both roles involve working with data and machine learning, Junior Machine Learning Engineers focus on building and deploying models, often with coding and engineering skills. Data Scientists analyze data, create statistical models, and interpret insights. The roles overlap but differ mainly in their core responsibilities and skill emphasis.

How much do junior machine learning engineers make?

Junior machine learning engineers typically earn between $70,000 and $100,000 annually, depending on location, education, and industry. Entry-level roles often require knowledge of programming languages like Python and familiarity with machine learning frameworks such as TensorFlow or PyTorch.

What job categories do people searching Junior Machine Learning Engineer jobs in Whitewater, WI look for?

The top searched job categories for Junior Machine Learning Engineer jobs in Whitewater, WI are:

What cities near Whitewater, WI are hiring for Junior Machine Learning Engineer jobs?

Cities near Whitewater, WI with the most Junior Machine Learning Engineer job openings:

Infographic showing various Junior Machine Learning Engineer job openings in Whitewater, WI as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, 1% Contract, and 1% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $70,746 per year, or $34 per hour.

Senior Data Engineer - Remote

Experity

Machesney Park, IL • On-site, Remote

$110K - $150K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 8 days ago


Experity rating

8.5

Company rating: 8.5 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

79th of 245 rated software companies


Job description

Experity is a mission-driven team transforming on-demand healthcare across the U.S., empowering urgent care clinics with industry-leading software that makes care faster, easier, and more patient-focused. Joining us means doing meaningful work that directly improves the healthcare experience for millions-from helping families access care quickly to ensuring clinics run smoothly behind the scenes. If you want to make a real impact alongside innovative, dedicated teammates while contributing to a trusted platform that's becoming the operating system for on-demand care, Experity is the place to grow your career.
Why You'll Love Working Here
At Experity, great work starts with great people-and we go the extra mile to support our team with a culture of care, growth, and celebration:
  • Day-One Benefits: Health, dental/orthodontia, and vision coverage the moment you start.

  • Ownership & Impact: Be part of our success with a synthetic ownership program after one year.

  • Robust Support: Access our Employee Assistance Program for everything from mental wellness to financial coaching. Pets, planning a vacation, and more.

  • Recharge & Reconnect: Generous PTO, team events, family picnics, and holiday parties.

  • Career Growth: Development programs designed to help you thrive and grow.

  • Competitive Compensation: Including quarterly bonuses and 401(k) matching to invest in your future.

Position Type: Full-time
Compensation: $110,000-$150,000, based on experience
Location:
  • Remote: Team members who live within the U.S. but are not local within a commutable distance from one of our offices may work remotely, with occasional travel to an Experity office for meetings, team collaboration or as needed.

Position Overview
We are seeking a Senior Data Engineer to design, build, and operate scalable data pipelines and data platform capabilities that power Experity's analytics, AI/ML, and healthcare products.
This is a hands-on engineering role requiring strong expertise in data engineering, cloud technologies, distributed data processing, and software engineering. You will work closely with Data Engineering, Data Science, Machine Learning, Product, and Software Engineering teams to transform data from diverse sources into trusted, high-quality, and reusable data products.
As a senior member of the team, you will also provide technical leadership, mentor engineers, contribute to architecture and design decisions, and continuously improve the scalability, reliability, and efficiency of Experity's data ecosystem.
What You'll Do
Data Engineering & Platform
  • Design, build, and maintain scalable ETL/ELT pipelines for batch and near-real-time data processing.
  • Integrate data from databases, APIs, applications, event streams, and external sources into Experity's enterprise data platform.
  • Build reusable, high-quality data models and curated data products for analytics, reporting, AI/ML, and operational applications.
  • Develop complex data transformations and processing workflows using Python, SQL, Snowflake, and distributed data technologies.
  • Design data solutions for scalability, availability, resiliency, performance, and cost efficiency.

Engineering Excellence & DataOps
  • Develop reusable frameworks, libraries, and engineering patterns that improve developer productivity and data pipeline consistency.
  • Implement automated testing, CI/CD, Infrastructure as Code, and DataOps practices across data engineering workflows.
  • Build monitoring, alerting, data observability, and automated remediation capabilities to ensure pipeline reliability and data integrity.
  • Troubleshoot complex production issues and drive root-cause analysis and long-term improvements.
  • Continuously optimize data pipelines, queries, storage, and compute for performance and cost.

Data Quality, Governance & Security
  • Implement data quality, validation, lineage, and reconciliation controls across critical data pipelines.
  • Partner with Data Architecture, Governance, and Security teams to ensure data solutions follow enterprise standards.
  • Ensure healthcare data is handled securely and in accordance with applicable privacy, security, and compliance requirements.

Technical Leadership & Collaboration
  • Provide technical leadership through solution design, architecture discussions, code reviews, and engineering best practices.
  • Mentor Data Engineers and help improve engineering quality and technical capabilities across the team.
  • Partner with Data Scientists and Machine Learning Engineers to build reliable datasets, feature pipelines, and data infrastructure for AI/ML applications.
  • Collaborate with Product, Engineering, Analytics, and business stakeholders to translate requirements into scalable data solutions.
  • Maintain clear technical documentation for data pipelines, models, architecture, and operational processes.

Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related technical field.
  • 5+ years of experience building production-grade data pipelines, data platforms, and large-scale data processing solutions.
  • Advanced proficiency in Python and SQL with strong software engineering fundamentals.
  • Hands-on experience with Snowflake and cloud-based data platforms.
  • Experience with Kafka, Flink, or other distributed and streaming technologies.
  • Strong experience with AWS, including services such as S3, Lambda, Glue, Kinesis, or equivalent cloud technologies.
  • Experience designing and optimizing ETL/ELT pipelines, data models, and high-volume data processing workflows.
  • Experience with orchestration technologies such as Airflow or equivalent platforms.
  • Experience with CI/CD, Git, automated testing, and Infrastructure as Code.
  • Strong understanding of data quality, governance, security, observability, and production support.
  • Strong problem-solving, communication, and cross-functional collaboration skills.
  • A "full-stack mindset", not hesitating to do what it takes to solve a problem end-to-end

Preferred
  • Experience transforming data leveraging dbt, preferably dbt cloud.
  • Experience working in AI-native engineering environments and effectively leveraging AI-assisted development tools to improve engineering velocity, code quality, and operational efficiency.
  • Experience supporting Machine Learning and Generative AI workloads, including feature engineering and ML data pipelines.
  • Experience with Docker, Kubernetes, Terraform, or CloudFormation.
  • Experience with data cataloging, lineage, metadata management, and data observability platforms.
  • Experience in Healthcare, HealthTech, SaaS, or other regulated industries.

Why our team?
  • Build scalable data platforms that power healthcare products, analytics, Machine Learning, and Generative AI.
  • Solve challenging data problems involving large, complex, and highly valuable healthcare datasets.
  • Work with modern technologies including Snowflake, AWS, Python, Spark, and streaming platforms.
  • Collaborate closely with Data Engineering, Machine Learning, Data Science, Product, and Engineering teams.
  • Provide technical leadership while continuing to remain deeply hands-on with engineering.

Experity is committed to fostering a diverse, equitable, and inclusive workplace where innovation thrives through collaboration, diverse perspectives, and continuous learning.
Equal Opportunity Employer
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights notice from the Department of Labor.

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