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Data Annotation Engineer Jobs in Philadelphia, PA

Agilent

Head of Data Engineering, AI CoE

Wilmington, DE · On-site

$171K - $321K/yr

... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ... Solid-line management of AI Data Engineers deployed into pods. * Leads a team responsible for ...

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 · 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 ...

Agilent

Head of Data Engineering, AI CoE

Wilmington, DE · On-site

$171K - $321K/yr

... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ... Solid-line management of AI Data Engineers deployed into pods. * Leads a team responsible for ...

Slipstream IT

Statistical Analytical Programmer

PA · On-site +1

Strong programming skills in SAS , with R experience beneficial for data analysis, programming, and statistical workflows. Strong documentation skills, including code annotation, traceability, and ...

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

Data Annotation Engineer information

See Philadelphia, PA salary details

$52K

$148.8K

$198.8K

How much do data annotation engineer jobs pay per year?

As of Aug 6, 2026, the average yearly pay for data annotation engineer in Philadelphia, PA is $148,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,800.00 and $197,800.00 per year, depending on experience, location, and employer.

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.

What are the key skills and qualifications needed to thrive as a data annotation engineer?

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 is a data annotation engineer?

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 popular job titles related to Data Annotation Engineer jobs in Philadelphia, PA? For Data Annotation Engineer jobs in Philadelphia, PA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Philadelphia, PA look for? The top searched job categories for Data Annotation Engineer jobs in Philadelphia, PA are:
What cities near Philadelphia, PA are hiring for Data Annotation Engineer jobs? Cities near Philadelphia, PA with the most Data Annotation Engineer job openings:
Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in Philadelphia, PA as of August 2026, with employment types broken down into 68% Full Time, 9% Part Time, and 23% Contract. Highlights an 72% In-person, and 28% Remote job distribution, with an average salary of $148,801 per year, or $71.5 per hour.

Data Domain Architect Lead

JPMorganChase

Wilmington, DE • On-site

Full-time

Re-posted 3 days ago

Job description

Job Summary:
JPMorganChase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals. As a Data Domain Architect Lead, you will manage a team to develop machine learning solutions through data annotation, curation, and validation while collaborating with other teams to optimize training data for machine learning models.
Responsibilities:
• Manage and coach a team of Machine Learning Data Domain analysts to support data annotation and label data/content using annotation tools and analysis
• Partner with leads in Data Science, Engineering, and Analytics to develop strategies to optimize training data for machine learning models
• Lead efforts to identify patterns and trends in conversational data through Natural Language Processing and/or other computational linguistic approaches
• Collaborate with stakeholders on evaluating the quality of machine learning classification and other output
• Actively contribute to the team’s continuous learning mindset by bringing in new ideas and perspectives that stretch the thinking of the group
Qualifications:
Required:
• 6+ years of related experience in development of machine learning solutions
• Familiar with industry annotation and labeling methods
• Experience with various data modeling techniques and tools
• Familiar with Finance and Banking products
• Broad expertise in data technologies; i.e., data warehousing, data processing, data quality concepts, Business Intelligence tools and analytical tools, unstructured data, machine learning
• Excellent analytical and problem-solving skills and the ability to pay close attention to detail
• Experience using Python in working with and analyzing large real-world datasets
• Working knowledge of information and data retrieval
• Working knowledge of machine learning and artificial intelligence paradigms and libraries
• Familiar with Large Language Models (LLMs) and prompt engineering
Preferred:
• Masters or PhD in a related field, or Bachelors
• Technical understanding of common relational database systems; i.e., Teradata and Oracle
• Excellent command of the Structured Query Language (SQL)
• Knowledge of SAS or Scala, and Python languages
• Knowledge of Advanced Statistics
• Advanced analytical thinking and problem-solving skills
• Strong interpersonal & communication skills
Company:
With a history tracing its roots to 1799 in New York City, JPMorganChase is one of the world's oldest, largest, and best-known financial institutions—carrying forth the innovative spirit of our heritage firms in global operations across 100 markets. Founded in 2000, the company is headquartered in New York, USA, with a team of 10001+ employees. The company is currently Late Stage.

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