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Annotation Judge Jobs in New Jersey (NOW HIRING)

Annotation Judge information

What is an annotation judge?

An Annotation Judge is a professional who evaluates the quality and accuracy of labeled data, such as text, images, or audio, which has been annotated for use in machine learning and artificial intelligence projects. Their main responsibility is to review, verify, and ensure that the data annotations meet specific guidelines and standards. Annotation Judges play a critical role in improving the reliability of training datasets, which directly impacts the performance of AI systems. They often work closely with data annotators, quality assurance teams, and project managers to maintain high data quality.

What are the key skills and qualifications needed to thrive as an annotation judge, and why are they important?

To thrive as an Annotation Judge, you need strong analytical skills, attention to detail, and subject matter expertise relevant to the data being evaluated, usually supported by a degree in a related field. Familiarity with annotation platforms, data labeling tools, and quality assurance systems is typically required. Excellent communication, impartiality, and critical thinking help you provide clear feedback and maintain high annotation standards. These skills are crucial to ensure data accuracy and consistency, which directly impact the performance of machine learning models.

What are some common challenges faced by annotation judges, and how can they effectively overcome them?

Annotation Judges often face challenges such as maintaining impartiality, handling ambiguous or subjective data, and ensuring high consistency across large volumes of work. To overcome these, it’s essential to follow established guidelines closely, communicate regularly with team members for clarification, and participate in calibration sessions. Staying detail-oriented and seeking feedback can also help maintain accuracy and fairness in their assessments.

What is the difference between Annotation Judge vs Data Annotator?

AspectAnnotation JudgeData Annotator
CredentialsTypically requires basic education, sometimes certification in data labelingUsually requires similar or less formal education, often on-the-job training
Work EnvironmentOffice or remote, working with data labeling platformsOffice or remote, performing data labeling tasks
Industry UsageUsed across AI, machine learning, and data science projectsCommon in AI, machine learning, and data preparation workflows
Search & Comparison IntentOften compared for roles involving data review and quality controlCompared for entry-level data labeling roles

The main difference between an Annotation Judge and a Data Annotator lies in their roles. Annotation Judges typically review and validate annotations made by Data Annotators, ensuring quality and accuracy. Data Annotators perform the initial labeling of data. Both roles are essential in AI data pipelines, with Annotation Judges focusing on quality control and Data Annotators on data preparation.

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

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

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

The top searched job categories for Annotation Judge jobs in New Jersey are:

What cities in New Jersey are hiring for Annotation Judge jobs?

Cities in New Jersey with the most Annotation Judge job openings:

Infographic showing various Annotation Judge job openings in New Jersey as of June 2026, with employment types broken down into 67% Full Time, 30% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Team Leader - Data Engineering (Shared Infrastructure)

Bloomberg LP

Princeton, NJ • On-site

$120K - $144K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 26 days ago


Bloomberg rating

9.4

Company rating: 9.4 out of 10

Based on 11 frontline employees who took The Breakroom Quiz

12th of 246 rated software companies


Job description

Team Leader - Data Engineering (Shared Infrastructure)
Location
Princeton
Business Area
Data
Ref #
10051710
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 innovative workflow efficiencies, and we implement technology solutions to enhance our systems, products and processes - all while providing customer support to our clients.
Our Team:
The Data AI group brings innovative AI technologies into the Data organization while contributing deep financial domain expertise to the development of AI-powered products. We partner closely with stakeholders to align AI innovation with Bloomberg's strategic objectives, focusing on optimizing data workflows and elevating the quality, intelligence, and usability of the data that drives our products. Our work amplifies impact by delivering intelligent data solutions and domain-informed systems that enhance the capabilities and competitiveness of Bloomberg's offerings.
What's the Role?
We are seeking a Team Leader to drive our Shared Infrastructure programs within Data. This role is central to enabling scalable and responsible data workflows by leading a team passionate about reusable infrastructure, integration patterns, and operational standards across the organization. You will partner closely with Engineering, Product, and Data teams to identify high-impact opportunities, define and implement reusable solutions, and enable consistent, efficient workflows across a distributed set of teams. This includes crafting how capabilities such as automated evaluation and LLM-enabled annotation are adopted and integrated into production workflows, in close collaboration with partner teams who own underlying platforms.
The ideal candidate is a thoughtful and pragmatic leader who combines deep technical fluency with a systems-oriented approach and an interest in emerging data and LLM-based workflows. You are able to translate sophisticated, evolving needs into clear, reusable approaches and scalable patterns, and you are comfortable operating in environments where ownership is distributed across teams. You bring experience contributing to and scaling shared data systems or frameworks, with exposure to evaluation workflows and LLM-enabled pipelines, and a clear perspective on how these capabilities should be integrated into production environments. You excel at identifying patterns across disparate team needs and translating them into well-defined requirements, reusable solutions, and adoption strategies. You are effective at driving alignment and securing partner consensus, particularly in ambiguous environments where success depends on influence rather than direct ownership. You have a track record of building communities of practice and guiding teams toward consistent, scalable approaches without relying on formal authority.
We'll Trust You To:
  • Lead and develop a central team responsible for defining and delivering shared data infrastructure and reusable workflow patterns that improve consistency and efficiency across teams
  • Provide technical and strategic leadership, translating diverse team needs into clear requirements, scalable solutions, and well-defined approaches to data workflows, automated evaluation, and efficient annotation
  • Partner closely with Engineering, Product, and Data leaders to identify high-impact opportunities for shared capabilities, align on priorities, and ensure solutions can be optimally put into production within technical, compliance, and cost constraints
  • Act as a central point of coordination for cross-team needs, identifying common gaps, reducing duplication, and enabling consistent approaches without becoming a bottleneck or enforcement layer
  • Ensure shared components, frameworks, and patterns are well-designed, well-documented, and broadly adopted, with a focus on usability, scalability, and real-world impact
  • Mentor and develop data engineers, encouraging a culture of pragmatism, strong technical judgment, and a focus on building solutions that are both scalable and widely usable

You'll Need to Have:
  • Prior people leadership experience, ideally guiding teams working on technical, data, or infrastructure-related problems in multi-functional environments.
  • Strong technical judgment in data engineering and shared systems design, with the ability to engage credibly with engineering partners on architecture, trade-offs, and scalable solutions.
  • Experience designing and scaling shared frameworks, systems, or platform-like capabilities across multiple teams
  • Experience with LLM-enabled workflows or annotation pipelines.
  • Proven ability to operate in ambiguous, high-judgment environments, translating diverse needs into clear requirements and practical, scalable solutions
  • Proven track record of driving alignment and influencing partners across engineering, product, and data teams without direct authority
  • Strong analytical and decision-making skills, with a track record of delivering clear, well-reasoned, and impactful solutions

We'd Love to See:
  • Familiarity with evaluation or data quality frameworks
  • Exposure to regulated or cost-constrained environments
  • Experience partnering with engineering to scale prototypes into production
  • Background in platform, infrastructure, or centralized enablement teams
  • Experience contributing to communities of practice or developer enablement efforts

Salary Range = 135,000 - 230,000 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.
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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