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No Experience Machine Learning Data Annotation Jobs in Largo, FL

FL Data Scientist Striveworks is a leader in Machine Learning Operations for highly regulated ... machine learning, or related quantitative disciplines * Kubernetes knowledge/experience Interview ...

FL Data Scientist Striveworks is a leader in Machine Learning Operations for highly regulated ... machine learning, or related quantitative disciplines * Kubernetes knowledge/experience Interview ...

The Data Scientist is primarily responsible for supporting/leading AI-driven initiatives that will ... Experience in developing Machine Learning Models/ LLMs, streamlining ETL operations, Database ...

The Data Scientist is primarily responsible for supporting/leading AI-driven initiatives that will ... Experience in developing Machine Learning Models/ LLMs, streamlining ETLoperations, Database ...

... experience What Sets You Apart - Preference for at least one of the following fields of study ... Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS ...

New

Perform statistical modeling and machine learning cloud-based ML platforms. * Communicating complex ... Demonstrated experience applying data science methods to real-world data problems. * Proficiency in ...

No prior experience in AI is required -- your domain knowledge is what matters. Key ... Experience with AI, machine learning, or annotation projects related to biology or microbiology.

Showing results 21-40

No Experience Machine Learning Data Annotation information

See Largo, FL salary details

$32.1K

$104.9K

$168K

How much do no experience machine learning data annotation jobs pay per year?

As of Aug 7, 2026, the average yearly pay for no experience machine learning data annotation in Largo, FL is $104,922.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,200.00 and $116,300.00 per year, depending on experience, location, and employer.

What should I expect when collaborating with machine learning engineers as a data annotator with no prior experience?

As a data annotator working alongside machine learning engineers, you will play a vital role in preparing high-quality labeled data for model training. Engineers often provide clear guidelines and feedback on how to label or categorize data accurately, and they may hold regular check-ins to address questions and ensure consistency. While you may not need technical expertise, strong communication and attention to detail are essential, as your work directly impacts the performance of machine learning models. Over time, you’ll become familiar with annotation tools and may have the opportunity to take on more advanced tasks or quality assurance responsibilities.

What is a no experience machine learning data annotation job?

'No Experience Machine Learning Data Annotation' jobs are entry-level positions where individuals help label and categorize data used to train machine learning models. These roles do not require prior experience in data science or programming, making them accessible to beginners. Typical tasks may include tagging images, transcribing audio, or identifying objects in videos. These jobs are essential for improving the accuracy of AI systems and are often done remotely or on a flexible schedule.

What are the key skills and qualifications needed to thrive as a no experience machine learning data annotation specialist, and why are they important?

To succeed in a No Experience Machine Learning Data Annotation role, you need strong attention to detail, basic computer literacy, and the ability to follow precise instructions, often requiring at least a high school diploma. Familiarity with data labeling tools (like Labelbox or Supervisely) and experience with spreadsheet software are typically helpful, though many positions offer on-the-job training. Reliability, patience, and effective communication are valuable soft skills for maintaining quality and meeting deadlines. These skills ensure accurate, consistent data labeling, which is critical for training reliable machine learning models.

What is the difference between No Experience Machine Learning Data Annotation vs Data Labeling Specialist?

AspectNo Experience Machine Learning Data AnnotationData Labeling Specialist
Required CredentialsNo formal experience needed, training providedTypically similar, may require basic technical skills
Work EnvironmentRemote or office-based, repetitive tasksRemote or onsite, focused on data preparation
Industry UsageCommon in AI/ML companies, tech startupsUsed across tech, automotive, healthcare sectors
Search & Comparison IntentOften searched by beginners or entry-level job seekersCompared for skill requirements and job scope

Both roles involve labeling data for machine learning models, with minimal experience required. Data Labeling Specialists may have slightly more specialized tasks, but both are entry-level positions vital for AI development.

What job categories do people searching No Experience Machine Learning Data Annotation jobs in Largo, FL look for? The top searched job categories for No Experience Machine Learning Data Annotation jobs in Largo, FL are:
Infographic showing various No Experience Machine Learning Data Annotation job openings in Largo, FL as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 19% Part Time, and 4% Contract. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $104,922 per year, or $50.4 per hour.

Machine Learning Engineer (PhD Intern)

Instacart

Saint Petersburg, FL

Full-time

Re-posted 17 days ago


Instacart rating

7.1

Company rating: 7.1 out of 10

Based on 31 frontline employees who took The Breakroom Quiz

27th 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