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Full Time Machine Learning Data Annotation Jobs in Fort Wayne, IN

Techo-Bloc

Production Machine Operator

Waterloo, IN · On-site

$29.68/hr

If you like staying busy, learning new machines, and seeing the results of your work every day ... Strong Data Driven core, with a proven ability to communicate performance, quality, safety, and ...

New

Lasting Change, Inc

AI Engineer

Fort Wayne, IN · On-site

Familiarity with MLOps concepts and an interest in growing into machine learning model development and deployment over time. * Exposure to healthcare, human services, or nonprofit data environments.

Lasting Change Inc

AI Engineer

Fort Wayne, IN

Familiarity with MLOps concepts and an interest in growing into machine learning model development and deployment over time. * Exposure to healthcare, human services, or nonprofit data environments.

U.S. Navy

Linguist

Garrett, IN · On-site

... data. • Analyze and report highly technical intelligence for fleet commanders and national ... machine learning systems. • Perform temporary duty aboard Navy surface ships and submarines ...

U.S. Navy

Linguist

Huntertown, IN · On-site

... data. • Analyze and report highly technical intelligence for fleet commanders and national ... machine learning systems. • Perform temporary duty aboard Navy surface ships and submarines ...

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All JobsMachine Learning Data Annotation JobsFull Time Machine Learning Data Annotation JobsFull Time Machine Learning Data Annotation Jobs in Fort Wayne, IN

Full Time Machine Learning Data Annotation information

See Fort Wayne, IN salary details

$37K

$121.1K

$193.9K

How much do full time machine learning data annotation jobs pay per year?

As of Sep 10, 2026, the average yearly pay for full time machine learning data annotation in Fort Wayne, IN is $121,100.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,200.00 and $134,200.00 per year, depending on experience, location, and employer.

What is a full time machine learning data annotation job?

Full time machine learning data annotation jobs involve labeling, tagging, or categorizing data such as images, text, audio, or video to help train machine learning models. Data annotators play a crucial role in ensuring that AI systems learn from high-quality, accurately labeled datasets. These positions often require attention to detail, consistency, and sometimes familiarity with the subject matter or specialized tools. Full-time roles may be remote or onsite and can span industries like autonomous vehicles, healthcare, retail, and more.

What are some common challenges faced by machine learning data annotators, and how are these typically addressed within a team?

Machine learning data annotators often encounter challenges such as maintaining consistency in labeling, handling ambiguous data, and meeting tight deadlines for large datasets. Teams usually address these by establishing clear annotation guidelines, conducting regular training sessions, and implementing quality assurance processes like peer reviews and spot checks. Collaboration with data scientists and project managers is also common, ensuring that annotators can ask questions and clarify uncertainties, leading to higher-quality labeled data and a supportive work environment.

What are the key skills and qualifications needed to thrive as a full time machine learning data annotation specialist, and why are they important?

To thrive as a Full Time Machine Learning Data Annotation Specialist, you need strong attention to detail, basic data literacy, and familiarity with data labeling concepts, often supported by a high school diploma or equivalent. Proficiency in specialized annotation platforms, spreadsheet tools, and sometimes knowledge of Python or labeling frameworks is typically required. Reliability, patience, and effective communication are valuable soft skills for ensuring accuracy and collaborating with team members. These skills and qualities are crucial because they directly impact the quality of training data, which is essential for developing effective machine learning models.

What is the difference between Full Time Machine Learning Data Annotation vs Data Labeling Specialist?

AspectFull Time Machine Learning Data AnnotationData Labeling Specialist
CredentialsHigh school diploma or equivalent; some roles prefer technical certificationsHigh school diploma or equivalent; training often provided on the job
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or office; focused on labeling tasks
Industry UsageUsed across AI/ML companies, tech firms, and startupsCommon in AI/ML, data services, and outsourcing companies
Job FocusCreating labeled datasets for machine learning modelsAnnotating data such as images, videos, or text for AI training

Full Time Machine Learning Data Annotation involves creating high-quality labeled datasets for AI models, often requiring technical understanding. Data Labeling Specialists focus on annotating data accurately, typically with less emphasis on technical skills. Both roles are essential in AI development but differ mainly in scope and technical complexity.

What are popular job titles related to Full Time Machine Learning Data Annotation jobs in Fort Wayne, IN?

For Full Time Machine Learning Data Annotation jobs in Fort Wayne, IN, the most frequently searched job titles are:

What job categories do people searching Full Time Machine Learning Data Annotation jobs in Fort Wayne, IN look for?

The top searched job categories for Full Time Machine Learning Data Annotation jobs in Fort Wayne, IN are:

Full Time Machine Learning Data Annotation jobs near you
Infographic showing various Full Time Machine Learning Data Annotation job openings in Fort Wayne, IN as of July 2026, with employment types broken down into 1% As Needed, 16% Full Time, 10% Part Time, 67% Contract, and 6% Nights. Highlights an 4% Physical, and 96% Remote job distribution, with an average salary of $121,100 per year, or $58.2 per hour.

Strategic Student Program: AI & Engineering Data Internship (Spring 2027, GSCS)

Fort Wayne, IN • Remote

Siemens
Machinery Manufacturing • 10K+ employees
Learn more about Siemensexternal

$18 - $50/hr

Full-time, Internship

Retirement

Posted 7 days ago

Siemens rating

7.7

Company rating: 7.7 out of 10

Based on 100 frontline employees who took The Breakroom Quiz

Job description

Siemens Digital Industries Software

Strategic Student Program (SSP)

Discover your career with us at Siemens Digital Industries Software!

We are a leading global software company dedicated to the world of computer aided design, 3D modeling and simulation- helping innovative global manufacturers design better products, faster! With the resources of a large company, and the energy of a software start-up, we have fun together while creating a world class software portfolio. Our culture encourages creativity, welcomes fresh thinking and focuses on growth, so our people, our business, and our customers can achieve their full potential.

We're currently recruiting co-ops and interns for our Spring 2027 Strategic Student Program. Our opportunities will allow you to find a career path that most inspires you. Here, you will apply your education to solve real-world problems and turn theory into practice. At Siemens, our goal is to empower our students to become the next leaders of our company.

Baseline Program Requirements:

  • Currently enrolled as an undergraduate student at an accredited university
  • Legally authorized to work in the United States without the need for current or future sponsorship by the company
  • A minimum 3.0 GPA

Perks:

  • Employee discounts at our top customer sites
  • Networking with our global leaders
  • Mentorship from senior employees
  • Individual career development planning
  • Professional and technical workshops
  • Paid volunteer time off
  • Energetic student community
  • Leadership opportunities
  • Potential for full-time offers after university graduation and completion of the program

Position Overview:

Siemens Digital Industries Software is seeking an AI & Engineering Data Intern to support emerging Artificial Intelligence and Digital Thread initiatives within the Capital PreSales organization. This role provides hands-on experience applying AI technologies to engineering challenges across aerospace, defense, and automotive industries.

The intern will help create and manage engineering datasets, investigate AI-assisted workflows, and support projects that demonstrate how Digital Threads enable intelligent decision-making throughout the product lifecycle. The role combines engineering, software, data management, and AI technologies to develop innovative customer-facing demonstrations and internal capabilities.

Key Responsibilities:

  • Develop and curate engineering datasets for AI, analytics, and demonstration use cases.
  • Support AI and generative AI proof-of-concepts involving engineering and Digital Thread data.
  • Assist in connecting systems, software, and electrical engineering information into reusable data models.
  • Evaluate and document AI-assisted engineering workflows and use cases.
  • Build dashboards, reports, and visualizations that communicate engineering insights.
  • Support technical enablement activities and customer demonstration development.

Requirements:

  • Pursuing a Bachelor's or Master's degree in Computer Science, Data Science, Artificial
  • Comfortable working in a fully remote environment within the United States of America.
  • Intelligence, Software Engineering, Systems Engineering, or a related discipline.
  • Experience with Python, data analytics, machine learning, or AI technologies.
  • Familiarity with digital engineering, PLM, or engineering data management concepts is a plus.
  • Strong communication, collaboration, and problem-solving skills.
  • Passion for applying emerging technologies to real-world engineering challenges.

#LI-PLM

#LI-Remote

#SWSaaS

You'll Benefit From

The hourly pay range for this position $18 - $50 per hour, based off of your projected graduation year. The actual wage offered may be lower or higher depending on budget and candidate experience, knowledge, skills, qualifications, and premium geographic location. Additionally, interns for Siemens are eligible to contribute into our 401K program.

Equal Employment Opportunity Statement

Siemens is an Equal Opportunity Employer encouraging inclusion in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.

EEO is the Law

Applicants and employees are protected from discrimination on the basis of race, color, religion, sex, national origin, or any characteristic protected by Federal or other applicable law.

Reasonable Accommodations

If you require a reasonable accommodation in completing a job application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please fill out the accommodations form by clicking on this link Accommodation for disability form. If you're unable to complete the form, you can reach out to our AskHR team for support at 1-866-743-6367. Please note our AskHR representatives do not have visibility of application or interview status.

Pay Transparency

Siemens follows Pay Transparency laws.

Application Deadline

This role will be posted for a minimum of five (5) days from the original posting date. The posting timeline may change based on applicant volume to ensure we attract and consider a strong and representative candidate pool.

California Privacy Notice

California residents have the right to receive additional notices about their personal information. To learn more, click here.

Criminal History

Qualified applications with arrest or conviction records will be considered for employment in accordance with applicable local and state laws.

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