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Data Annotation Engineer Jobs in Philadelphia, PA

Chase

Data Domain Architect Lead

Wilmington, DE · On-site

... and Engineering to develop machine learning solutions. This will involve the collection, curation, annotation, enrichment, and validation of data and the development of taxonomies and other ...

General Motors

Senior AI/ML Engineer

Trenton, NJ · On-site +1

$104.80K - $143.90K/yr

Apply ML to labeling itself Collaborate with ML engineers to design and integrate ML-driven data annotation (pre-labeling, autolabeling, active learning loops), helping us move from human-only to ...

Forhyre

Prompt Engineers

Philadelphia, PA

As a Prompt Engineer, you will be a key member of our AI development team, responsible for ... Solid knowledge of data collection, preprocessing, and annotation for prompt development.

URBN

URBN Senior Data Scientist

Philadelphia, PA · On-site

... annotation workflows, and synthetic data generation. * Analyze and benchmark model outputs for ... Partner with engineers to translate research prototypes into production-grade services and APIs ...

URBN

URBN Senior Data Scientist

Philadelphia, PA

... annotation workflows, and synthetic data generation. * Analyze and benchmark model outputs for ... Partner with engineers to translate research prototypes into production-grade services and APIs ...

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All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in Philadelphia, PA

Data Annotation Engineer information

See Philadelphia, PA salary details

$49.2K

$140.9K

$188.3K

How much do data annotation engineer jobs pay per year?

As of May 28, 2026, the average yearly pay for data annotation engineer in Philadelphia, PA is $140,932.00, according to ZipRecruiter salary data. Most workers in this role earn between $80,300.00 and $187,300.00 per year, depending on experience, location, and employer.

What is a Data Annotation Engineer job?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by Data Annotation Engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.
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Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Philadelphia, PA as of May 2026, with employment types broken down into 5% As Needed, 67% Full Time, 23% Part Time, and 5% Contract. Highlights an 51% Physical, and 49% Remote job distribution, with an average salary of $140,932 per year, or $67.8 per hour.
Data Pipeline Technician - Pennsauken, NJ

Data Pipeline Technician - Pennsauken, NJ

Kett Engineering

Pennsauken, NJ • On-site

$28 - $30/hr

Other

This job post has expired today. Applications are no longer accepted.

Job description

Data Pipeline Technician - Pennsauken, NJ

Salary Range $28.00 - $30.00 Hourly

Description

Summary

Data Pipeline Technicians execute and maintain the data pipeline processes designed by engineers, ensuring timely and accurate data delivery for AI development.

Responsibilities
  • Plan and execute data collection activities, including log road trips to gather real-world driving data across varied environments.
  • Operate and maintain specialized data collection vehicles and equipment.
  • Ingest, clean, and prepare data for annotation and AI training.
  • Perform maintenance of the AI fleet and verify quality of annotated data.
  • Ensure timely and accurate delivery of data to engineering teams.
  • Support operational needs of Engineering and other departments by providing reliable data and technical assistance.
Impact

Their reliability and attention to detail ensure the smooth operation of OEMs data-driven AI development, while also supporting data needs across the organization.

Required Skills
  • Data Collection and Management – ability to plan and execute large-scale data collection activities, including real-world driving scenarios.
  • Vehicle and Equipment Operation – skilled in operating and maintaining specialized data collection vehicles and hardware.
  • Data Processing – Experience in ingesting, cleaning, and preparing data for annotation and AI training.
  • Quality Assurance – ability to verify accuracy and completeness of annotated data.
  • Technical Reliability – ensure timely and accurate delivery of data to engineering teams.
  • Attention to Detail – maintain precision in data handling and equipment maintenance.
  • Collaboration and Support – Provide technical assistance to engineering and other departments.
Preferred Skills
  • Familiarity with AI development workflows and data annotation processes.
  • Basic knowledge of data pipeline tools and scripting (e.g. Python, Bash).
  • Understanding of vehicle systems and sensor technologies.
  • Experience with Fleet management and preventative maintenance practices.
  • Ability to troubleshoot hardware/software issues in data collection environments.

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