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Internship Online Data Annotation Jobs in Wisconsin

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

This paid, part-time internship (15-25 hours per week during normal office hours) begins summer ... Proofread social media posts via Hootsuite * Assist with monitoring and reporting online mentions ...

New

Showing results 21-40

Internship Online Data Annotation information

What is the difference between Internship Online Data Annotation vs Data Labeling Specialist?

AspectInternship Online Data AnnotationData Labeling Specialist
CredentialsTypically students or entry-level with basic computer skillsUsually requires experience or training in data labeling tools
Work EnvironmentRemote, flexible, often part-timeRemote or on-site, depending on employer
Industry UsageCommon in AI/ML projects, tech companiesUsed in AI, autonomous vehicles, healthcare, and more

Internship Online Data Annotation roles are often entry-level, focusing on training and learning, while Data Labeling Specialists are more experienced, handling complex labeling tasks. Both roles are essential in AI development but differ in experience requirements and scope.

What are the key skills and qualifications needed to thrive as an internship online data annotation?

To thrive as an Internship Online Data Annotation, you generally need attention to detail, basic computer skills, and a high school diploma or equivalent. Familiarity with annotation platforms, data labeling tools, and sometimes Excel or similar spreadsheet software is typically required. Strong communication, reliability, and the ability to follow precise instructions make candidates stand out in this role. These skills ensure high-quality, accurate data labeling, which is vital for training reliable machine learning models.

What is an internship online data annotation?

Internship Online Data Annotation positions are temporary roles, often held by students or recent graduates, where individuals label and categorize data such as images, text, or audio for use in machine learning and artificial intelligence projects. Interns work remotely or in-office to ensure data is accurately annotated according to project guidelines, helping to train and improve AI models. These internships provide hands-on experience in data management, attention to detail, and exposure to AI technologies. They are ideal for those interested in technology, data science, or AI fields, and can be a stepping stone to more advanced roles.

What types of data and tools will I typically work with during an internship online data annotation?

As an Online Data Annotation intern, you'll commonly work with a variety of data types such as text, images, audio, or video, depending on the project's focus. You'll use specialized annotation platforms or software to label and categorize data accurately for use in machine learning models. Interns often collaborate with data scientists and engineers to understand project requirements and ensure high-quality outputs. Attention to detail and following precise guidelines are key challenges in this role, but you'll gain valuable exposure to real-world AI development workflows.

What are the most commonly searched types of Online Data Annotation jobs in Wisconsin?

The most popular types of Online Data Annotation jobs in Wisconsin are:

What are popular job titles related to Internship Online Data Annotation jobs in Wisconsin?

For Internship Online Data Annotation jobs in Wisconsin, the most frequently searched job titles are:

What job categories do people searching Internship Online Data Annotation jobs in Wisconsin look for?

The top searched job categories for Internship Online Data Annotation jobs in Wisconsin are:

What cities in Wisconsin are hiring for Internship Online Data Annotation jobs?

Cities in Wisconsin with the most Internship Online Data Annotation job openings:

Machine Learning Engineer (PhD Intern)

Instacart

Racine, WI • On-site

Other

Re-posted 24 days ago


Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

28th of 64 rated delivery companies


Job description

We're transforming the grocery industry

At Instacart, we invite the world to share love through food because we believe everyone should have access to the food they love and more time to enjoy it together. Where others see a simple need for grocery delivery, we see exciting complexity and endless opportunity to serve the varied needs of our community. We work to deliver an essential service that customers rely on to get their groceries and household goods, while also offering safe and flexible earnings opportunities to Instacart Personal Shoppers.

Instacart has become a lifeline for millions of people, and we’re building the team to help push our shopping cart forward. If you’re ready to do the best work of your life, come join our table.

Instacart is a Flex First team

There’s no one-size fits all approach to how we do our best work. Our employees have the flexibility to choose where they do their best work—whether it’s from home, an office, or your favorite coffee shop—while staying connected and building community through regular in-person events.

Overview

Since 2012, Instacart has been focused on making grocery delivery convenient, affordable, and accessible to everyone. We bring fresh groceries and everyday essentials to customers across the US and Canada from nearly 55,000 stores across 5,500 markets. Our mission is to create a world where everyone has access to the food they love, and to achieve that goal, we innovate in a wide range of areas including e-commerce, advertising, and fulfillment.

We use machine learning and Internet-scale data to elevate customer experience, improve efficiency, and reduce cost. As an example, we manage catalog data imported from hundreds of retailers, and we build product and knowledge graphs on top of the catalog data to support a wide range of applications including search and ads.

We are looking for talented Ph.D. students to have an internship in our fast moving team. You will have the opportunity to work on a very large scope of problems in search, ads, personalization, recommendation, fulfillment, product and knowledge graph, pricing, etc.

About the Team:

This is a general posting for multiple intern roles open across our various ML teams. You can find a blurb on each team below:

Economics Team: The Economics team at Instacart works on a range of interesting and challenging problems, from aligning the incentives in our multi-sided marketplace to analyzing the role of prices and product placement in our customers' decision-making. Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference.

Search & Discovery ML: The Search and Discovery ML team at Instacart works alongside world-class engineers, data scientists, and product managers to shape the future of search technology at Instacart. They collaborate on building models that enhance relevance of all shopping surfaces, ranking, and personalization, delivering highly relevant results to users across the Instacart ecosystem. As part of the Search and Discovery ML team, you'll work on one of the most critical aspects of the business, helping customers connect with the right products. We are passionate about solving large-scale search challenges and creating innovative solutions that elevate the customer experience. (Recent publications 1, 2, 3, 4, 5).

Content AI Team: The Content AI team at Instacart works alongside world-class engineers, data scientists, and product managers to advance generative AI, recommendations, and catalog intelligence in grocery ecommerce. We build cutting-edge AI models that power real-time recommendations, feed ranking, and automated content generation, ensuring high-quality and engaging customer experiences. Beyond recommendations, we leverage generative AI and LLMs to enhance and enrich Instacart’s catalog, driving AI-powered product understanding and content creation at scale. As part of Content AI, you'll work on high-impact AI solutions, applying LLMs, agentic systems, and computer vision to tackle complex challenges. We are passionate about pushing the boundaries of generative AI to shape the future of ecommerce. If you're excited about building state-of-the-art AI systems, we’d love to have you on board!

Past internship contributions include:

Tensor-based complementary recommendations, published at IEEE Big Data 2021 (Paper) Enhancing sequence-based recommendations for long-tail products (Blog)

About the Job

Based on your passion and background, you may choose to work in a few different areas:

  • Query understanding - Using cutting-edge NLP technologies to understand the intent of user queries.
  • Search relevance and ranking - Improving search relevance by incorporating signals from various sources.
  • Ads quality, pCTR, etc. - Improving ads revenue and ROAS.
  • Knowledge graphs - Working on graph data management and knowledge discovery, and creating a natural language interface for data access.
  • Fraud detection and prevention - Using cost sensitive learning to reduce loss.
  • Pricing - Estimating willingness-to-pay, and optimizing revenue and user experience.
  • Logistics - Optimization in a variety of situations, including supply/demand prediction, last mile delivery, in-store optimization, etc.

About You

Minimum Qualifications:

  • Ph.D. student in computer science, mathematics, statistics, economics, or related areas.
  • Strong programming (Python, C++) and algorithmic skills.
  • Good communication skills. Curious, willing to learn, self-motivated, hands-on.

Preferred Qualifications:

  • Ph.D. student at a top tier university in the United States
  • Prior internship/work experience in the machine learning space

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role.


What Instacart employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Instacart logo

About Instacart

Sourced by ZipRecruiter

Instacart, based in San Francisco, CA, US, operates within the retail industry, specifically grocery delivery and pick-up service. It is recognized as a pioneer in this field, delivering fresh groceries from local stores directly to customers' doors. The company, which launched its services in 2012, continues to pioneer change in the online grocery shopping sector through its commitment to cutting-edge technology, new business ideas, and dedicated service.

Industry

Technology, communication and media

Company size

10,000+ Employees

Headquarters location

San Francisco, CA, US

Year founded

2012