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Weekend Ai Data Annotation Jobs in New Jersey (NOW HIRING)

We believe in the power of automation and thoughtfully applied AI/ML to solve problems beyond the ... Data Annotation : Generate highly precise, objective sensory data by performing character and ...

We believe in the power of automation and thoughtfully applied AI/ML to solve problems beyond the ... Data Annotation : Generate highly precise, objective sensory data by performing character and ...

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Weekend Ai Data Annotation information

What is a Weekend AI Data Annotation specialist?

Weekend AI Data Annotators are professionals who label, categorize, and tag data—such as images, audio, or text—for use in training artificial intelligence models, specifically working on weekends. Their work ensures that machine learning algorithms receive high-quality, accurately labeled datasets for tasks like computer vision, natural language processing, or speech recognition. This role often involves using specialized annotation tools and following precise guidelines to maintain consistency and accuracy. Weekend annotators may work remotely or on-site, and their contributions are vital for improving AI system performance.

What skills and qualifications are needed to thrive as a Weekend AI Data Annotation specialist?

To thrive as a Weekend AI Data Annotation Specialist, you need attention to detail, strong analytical skills, and familiarity with data labeling processes, often supported by a high school diploma or post-secondary coursework in a technical field. Proficiency with annotation platforms like Labelbox, Supervisely, or internal company tools is typically required, along with basic knowledge of data privacy protocols. Reliability, time management, and effective communication are crucial soft skills for meeting project deadlines and collaborating with remote teams. These skills and qualities ensure the accuracy and efficiency of annotated datasets, which are essential for high-performing AI systems.

What are common challenges faced by Weekend AI Data Annotation specialists, and how can they be managed?

Weekend AI Data Annotation specialists often encounter challenges such as maintaining high attention to detail during repetitive tasks and managing productivity over long annotation sessions. Since the work is typically remote or semi-remote, self-motivation and effective time management are crucial to meet project deadlines. It's helpful to take regular breaks, communicate proactively with team leads when questions arise, and make use of any annotation guidelines or quality assurance feedback provided. Collaborating with teammates through chat platforms or project management tools can also enhance consistency and resolve uncertainties quickly.

What are the most commonly searched types of Ai Data Annotation jobs in New Jersey?

The most popular types of Ai Data Annotation jobs in New Jersey are:

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

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

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

The top searched job categories for Weekend Ai Data Annotation jobs in New Jersey are:

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

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

Senior Data Management Professional - Data Engineering (Data AI)

Bloomberg LP

Princeton, NJ • On-site

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 15 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

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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Bloomberg logo

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