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Entry Level Machine Learning Data Annotation Jobs

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

Amazon

Catalog Specialist, RCX

Bellevue, WA · On-site

Key job responsibilities • Work closely with our product, technology, and science teams to support Machine Learning (ML) models • Perform data annotation required to train and evaluate ML models ...

TSMG

AI/ML Data Contributor

Louisville, KY · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Los Angeles, CA · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Boise, ID · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Birmingham, AL · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Birmingham, AL

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Louisville, KY · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Columbia, SC · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Des Moines, IA · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Jackson, MS · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Chicago, IL · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Columbia, SC · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Philadelphia, PA · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Boise, ID · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Wichita, KS · On-site

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

TSMG

AI/ML Data Contributor

Fargo, ND · Remote

Previous experience in data annotation, QA, or testing * Interest in AI, machine learning, or emerging technologies What We Offer * Paid, flexible task-based work * Opportunity to work on innovative ...

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All JobsEntry Level Machine Learning Data Annotation Jobs

Entry Level Machine Learning Data Annotation information

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$31

How much do entry level machine learning data annotation jobs pay per hour?

As of Jun 25, 2026, the average hourly pay for entry level machine learning data annotation in the United States is $20.24, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $21.88 per hour, depending on experience, location, and employer.

How hard is it to get hired at data annotation?

Getting hired for an entry-level machine learning data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools. The hiring process is often straightforward, with many positions offering flexible schedules and minimal experience requirements, making it accessible for beginners.

Can you work for data annotation with no experience?

Entry level machine learning data annotation roles often do not require prior experience, as training is typically provided to teach specific annotation tools and guidelines. Basic computer skills, attention to detail, and the ability to follow instructions are usually sufficient to start, making it accessible for beginners. However, some positions may prefer familiarity with data labeling or related tasks.

Is DataAnnotation legit in 2026?

Data annotation is a legitimate and essential part of entry-level machine learning jobs, including data annotation roles. These positions typically involve labeling data for training AI models and require attention to detail, basic understanding of data formats, and sometimes familiarity with annotation tools. The field remains active, with ongoing demand for skilled annotators in AI development.

Does data annotation really pay you?

Entry level machine learning data annotation jobs typically pay hourly or per task rates, with pay varying based on complexity and platform. Many roles offer part-time or flexible schedules, and payment is usually processed through direct deposit or online payment systems. Overall, data annotation can provide a reliable income for those with attention to detail and basic computer skills.

What is the difference between Entry Level Machine Learning Data Annotation vs Entry Level Data Labeling Specialist?

AspectEntry Level Machine Learning Data AnnotationEntry Level Data Labeling Specialist
CredentialsBasic understanding of data annotation tools, no formal certification requiredSimilar; often no formal certification needed
Work EnvironmentRemote or on-site, working with AI teams and datasetsRemote or on-site, focusing on labeling data for AI/ML projects
Industry UsagePrimarily in AI, machine learning, and data science companiesUsed across tech, automotive, healthcare, and other industries
Search & Comparison IntentCommonly compared for entry-level roles in AI data prepOften compared as a similar entry-level data labeling role

Both roles involve preparing data for machine learning models, with similar entry-level requirements. The main difference lies in terminology and specific job focus, but they often overlap in skills and work environment.

More about Entry Level Machine Learning Data Annotation jobs
What cities are hiring for Entry Level Machine Learning Data Annotation jobs? Cities with the most Entry Level Machine Learning Data Annotation job openings:
What are the most commonly searched types of Machine Learning Data Annotation jobs? The most popular types of Machine Learning Data Annotation jobs are:
What states have the most Entry Level Machine Learning Data Annotation jobs? States with the most job openings for Entry Level Machine Learning Data Annotation jobs include:
What job categories do people searching Entry Level Machine Learning Data Annotation jobs look for? The top searched job categories for Entry Level Machine Learning Data Annotation jobs are:
Entry Level Machine Learning Data Annotation jobs near you
Infographic showing various Entry Level Machine Learning Data Annotation job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, and 16% Part Time. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $42,098 per year, or $20.2 per hour.

Software Engineer, Machine Learning Infrastructure

Bot Auto

Houston, TX • On-site

$165K - $195K/yr

Full-time

Posted 16 days ago

Job description

Company Introduction
At Bot Auto, we are revolutionizing the transportation of goods with our cutting-edge autonomous trucks, enhancing the quality of life for communities around the globe. With the agility of a start-up and the wisdom of seasoned experts, Bot Auto boasts a team that has achieved numerous world-firsts and unparalleled innovations. United by a shared vision, we create miracles and propel the future of transportation. Join us and transform your dreams into reality.
We are seeking a highly skilled and motivated Software Engineer to design, develop, and scale our machine learning annotation, evaluation, and training infrastructure. This role is central to the quality and velocity of our perception and ML models - from curating and managing high-quality annotated datasets, to building robust evaluation pipelines that drive continuous model improvement. The ideal candidate combines strong systems engineering skills with a deep understanding of ML Workflows/Ops and large-scale data infrastructure.
Key Responsibilities
Machine Learning & Deep Learning Infrastructure
  • Evaluation Platform - Architect and own a scalable, end-to-end model evaluation platform for perception and prediction models central to autonomous driving. Define metrics, design for scale, and make results actionable for researchers.
  • Training Infrastructure - Partner with research scientists to optimize and scale distributed training workflows. Integrate experiment tracking and reproducibility into the model lifecycle from day one.
  • Dataset & Feature Store - Design and maintain a versioned, high-quality training data store that accelerates model development and supports rapid iteration.
  • ML Pipelines - Build automated pipelines spanning data preparation, model training, validation, and deployment - enabling fast experimentation and reproducible outcomes.
  • Annotation Platform - Contribute to tooling and infrastructure that powers high-throughput, high-accuracy data annotation at scale.
  • MLOps - Develop production ML services that treat models as products - with reliability, observability, and continuous improvement built in.

Data Infrastructure
  • Maintain and evolve a robust data storage and access layer (S3 data lake, Delta Lake) underpinning annotation, evaluation, and training workflows.
  • Build scalable, reliable data collection pipelines supporting diverse vehicle dispatch missions.
  • Develop foundational services and packages that provide clean, performant access to autonomous driving data across the stack.
Qualifications
Required:
  • Educational Background: Bachelor's or Master's in Computer Science, or equivalent practical experience.
  • Strong Programming Skills: Strong proficiency in Python; working knowledge of C++
  • ML/DL Infrastructure Experience - Demonstrated hands-on experience building or scaling at least one of the following in a production environment:
    • Evaluation platforms - automated model benchmarking, metric computation, and regression tracking across model versions.
    • Training infrastructure - distributed training pipelines, experiment tracking, and model lifecycle management (e.g. W&B, MLflow, ClearML).
    • Dataset curation & feature stores - versioned dataset management, data lineage, and tooling for high-quality training data at scale.
    • Annotation platforms - tooling or pipelines that support high-throughput, high-accuracy labeling workflows.
  • Distributed Systems - Strong experience with distributed computing and container orchestration - Kubernetes, Spark, or comparable frameworks.
  • Ability to operate independently: scope ambiguous problems, make sound architecture decisions, and drive them to completion.

Preferred:
  • C++ experience in performance-sensitive or safety-critical applications
  • Full-stack service development experience.
  • Prior work in autonomous driving or robotics.

Apply