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Data Annotation Engineer Jobs in New Jersey (NOW HIRING)

AmNet Services, Inc.

NJ

Our founders are hardcore telecommunications engineers with combined 200 + years of experience in ... Whether an off-the-shelf or custom solution is needed, we'll create a solution and push the data on ...

Jj

Principal Scientist, Imaging Analytics

Raritan, NJ · On-site

  • Retirement

  • PTO

Ph.D. in Computer Science, Biomedical Engineering, Electrical Engineering, or a related ... imaging data workflow: DICOM I/O, visualization, registration, harmonization, annotation, and ...

All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in New Jersey

Data Annotation Engineer information

See New Jersey salary details

$52.3K

$149.7K

$200K

How much do data annotation engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for data annotation engineer in New Jersey is $149,708.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,300.00 and $199,000.00 per year, depending on experience, location, and employer.

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 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 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 is the salary of data annotation engineer?

The salary of a data annotation engineer typically ranges from $40,000 to $80,000 annually, depending on experience, location, and the complexity of annotation tasks. Entry-level positions may start lower, while experienced professionals with specialized skills in tools like Labelbox or CVAT can earn higher salaries.

What are popular job titles related to Data Annotation Engineer jobs in New Jersey?

For Data Annotation Engineer jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Data Annotation Engineer jobs in New Jersey look for?

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What cities in New Jersey are hiring for Data Annotation Engineer jobs?

Cities in New Jersey with the most Data Annotation Engineer job openings:

Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 11% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution, with an average salary of $149,708 per year, or $72 per hour.

Senior Data Management Professional - Data Engineering (Data AI)

Bloomberg LP

Princeton, NJ • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 4 days ago

Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

11th of 245 rated software companies

Job description

Senior Data Management Professional - Data Engineering (Data AI)
Location
Princeton
Business Area
Data
Ref #
10052626
Description & Requirements
Bloomberg runs on data. Our products are fueled by powerful information. We combine data and context to paint the whole picture for our clients, around the clock - from around the world. In Data, we are responsible for delivering this data, news, and analytics through innovative technology - quickly and accurately. We apply problem-solving skills to identify workflow efficiencies and implement technology solutions to enhance our systems, products, and processes.
Our Team:
Data AI contributes to the building of Bloomberg's AI-enhanced products at scale by curating model training data and enhancing how our internal processes use AI. We provide evaluation and annotation frameworks connecting natural language processing and human judgment in order to elevate the quality, intelligence, and usability of the data that drives our products.
By investing in AI at a strategic level, we expand our practice of engaging with AI to one that is embedded across Data. Our internal processes to take advantage of new AI technologies and strengthen Data's role in providing robust domain expertise and influential data artifacts to Bloomberg's products. As a result our clients will continue to have high quality data and access to new types of datasets.
The Role:
As a Data Engineer within Data AI, you will build and evolve the infrastructure, data pipelines, and operational tooling that power scalable AI and data workflows. You will enable reliable data collection, annotation, training, and evaluation processes by developing systems that improve data quality, operational visibility, and workflow efficiency. Through automation, observability, and platform engineering, you will help create the foundations that allow teams to deliver data and AI products with confidence and at scale.
We'll trust you to:
  • Design, build, and maintain scalable data pipelines that support data collection, annotation, training, evaluation, analytics, and reporting workflows.
  • Develop and operate systems for dataset management, storage, versioning, and lifecycle governance to ensure reliable and reproducible AI workflows.
  • Implement monitoring, observability, and alerting capabilities that provide visibility into data quality, system health, and operational performance.
  • Build dashboards, tooling, and self-service capabilities that improve transparency, efficiency, and decision-making across data operations.
  • Partner with Product, Engineering, and Data teams to evolve the infrastructure and platforms supporting AI-enabled products and workflows.
  • Identify bottlenecks and opportunities for automation, delivering scalable solutions that improve reliability, consistency, and operational efficiency.

You'll need to have:
  • Bachelor's degree in Finance, Business, Economics, Accounting, STEM or degree-equivalent qualifications
  • 3+ years in data engineering (Python, SQL)
  • Experience building ETL/data pipelines at scale and creating data collection frameworks for structured and unstructured data
  • Experience with data modeling and developing proactive data quality strategies that ensure data is fit for purpose
  • Experience working with ML/AI datasets or experimentation workflows.
  • Excellent problem-solving and analytical thinking skills with strong attention to detail.
  • Proven track record of stakeholder relationship management, communication, and cross-team collaboration.

We'd love to see:
  • Keen interest in and familiarity with generative AI frameworks and the requirements of Agentic AI.
  • Experience in semantic structures or large scale data modeling
  • Experience using data visualization tools such as Tableau, QlikSense, or PowerBI
  • Experience developing or managing annotation programs and training/evaluation datasets for ML or NLP models.
  • Deep domain expertise in financial markets/news and understanding of our customers' needs.

If this sounds like you:
Apply! If you think we're a good match. We'll get in touch to let you know the next steps!
Salary Range = 110,000 - 190,000 USD Annual + Benefits + Bonus
The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.
We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.
Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

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About Bloomberg

Sourced by ZipRecruiter

Bloomberg runs on data. As the Data Management & Analytics team within Engineering, we support our organization's needs around managing data efficiently. The vision of the team is to build solutions that drive data quality, data dictionary, data stewardship, data lineage, reference, and master data management across various data domains (prospect, customer, vendor, material etc.). We partner with business teams across the organization in addressing their data needs and ultimately helping run business operations efficiently and make improved decisions.

Industry

Finance and insurance

Company size

10,000+ Employees

Headquarters location

New York, NY, US

Year founded

1981

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