1

Data Annotation Jobs in Harrison, NJ (NOW HIRING)

Prior experience with data annotation , labeling, evaluation, or human feedback collection. * Experience with LLMs , AI systems , or agentic workflows; familiarity with agentic frameworks.

Prior experience with data annotation, labeling, evaluation, or human feedback collection. * Experience with LLMs , AI systems , or agentic workflows; familiarity with agentic frameworks. Application ...

Prior experience with data annotation, labeling, evaluation, or human feedback collection. * Experience with LLMs , AI systems , or agentic workflows; familiarity with agentic frameworks. Application ...

Who You Are Required Background * 5+ years working at the intersection of ML and data - annotation methodology, dataset curation, data-centric ML, ground truth design, or labeling-specifications work ...

Prior experience with RLHF, model evaluation, or data annotation work * Experience writing or editing high-quality written content * Experience comparing multiple outputs and making fine-grained ...

Experience with RLHF, model evaluation, or data annotation work * Experience writing or editing high-quality written content * Experience comparing multiple outputs and making fine-grained ...

Prior experience with RLHF, model evaluation, or data annotation work . * Experience writing or editing high-quality written content . * Experience comparing multiple outputs and making fine-grained ...

Prior experience with RLHF, model evaluation, or data annotation work . * Experience writing or editing high-quality written content . * Experience comparing multiple outputs and making fine-grained ...

Experience with RLHF, model evaluation, or data annotation work * Experience writing or editing high-quality written content * Experience comparing multiple outputs and making fine-grained ...

next page

Showing results 1-20

Data Annotation information

Is data annotation a legitimate?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It is commonly performed remotely and requires attention to detail, basic technical skills, and familiarity with annotation tools. Many companies hire data annotators as part of their AI development teams.

What does a typical workday look like for someone in a Data Annotation role?

A typical workday as a Data Annotator involves reviewing datasets—such as images, audio, text, or video—and accurately labeling or categorizing information according to specific project guidelines. Most Data Annotators work independently, but they often collaborate with project managers or data scientists to clarify requirements and resolve ambiguities. Tasks may be repetitive, but adhering to precise standards is vital for maintaining data quality. Work environments can range from technology companies to remote or freelance settings, and advancement opportunities exist as team leads or quality assurance specialists for those who excel in consistency and reliability.

What is a Data Annotation job?

A Data Annotation job involves labeling and categorizing data, such as text, images, audio, or video, to help train machine learning models. Annotators apply tags, bounding boxes, or classifications to data based on specific guidelines. This process improves the accuracy of AI systems in recognizing patterns and making predictions. Many data annotation jobs require attention to detail and familiarity with specific domains. It is commonly used in applications like autonomous driving, natural language processing, and computer vision.

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

To thrive in Data Annotation, you need strong attention to detail, accuracy, and basic data handling skills, often supported by a high school diploma or equivalent. Familiarity with annotation platforms, data labeling software, or content management systems is frequently required, though specific certifications are rare. Excellent communication, time management, and the ability to focus on repetitive tasks distinguish top performers in this role. These skills are crucial because accurate and consistent data annotation directly impacts the quality of machine learning models and AI applications.

What does a data annotator do?

A data annotator labels and tags data such as images, text, or videos to help machine learning models understand and learn from the data. They use tools and follow guidelines to ensure accuracy and consistency, often working with large datasets in a structured environment. Attention to detail and knowledge of annotation tools are important for this role.

Do people actually make money on data annotation?

Data annotation jobs can provide a source of income, with pay rates varying based on the complexity of tasks, platform, and experience. Many annotators earn hourly or per-task wages, but earnings often depend on the volume of work completed and the employer's pay structure.

Is it hard to get hired for data annotation?

Getting hired for a data annotation role generally depends on the employer's requirements, such as attention to detail and basic computer skills. Many positions are entry-level and may not require prior experience or certifications, making them accessible to a wide range of applicants. However, competition can vary based on the number of available jobs and the quality of applicants.
What are the most commonly searched types of Data Annotation jobs in Harrison, NJ? The most popular types of Data Annotation jobs in Harrison, NJ are:
What job categories do people searching Data Annotation jobs in Harrison, NJ look for? The top searched job categories for Data Annotation jobs in Harrison, NJ are:
What cities near Harrison, NJ are hiring for Data Annotation jobs? Cities near Harrison, NJ with the most Data Annotation job openings:
Infographic showing various Data Annotation job openings in Harrison, NJ as of June 2026, with employment types broken down into 1% As Needed, 87% Full Time, and 12% Part Time. Highlights an 45% Physical, 1% Hybrid, and 54% Remote job distribution.

Software Engineer (C#) - Internal Tooling

Alignerr

Manhattan, NY • Remote

Other

Posted 8 days ago


Job description

Software Engineer (C#) - Internal Tooling (AI Infrastructure)
About the Role
What if your C# expertise could directly shape the infrastructure powering the world's most advanced AI systems? We're looking for experienced C# full-stack engineers to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on.
This is a fully remote contract role with meaningful technical scope - real production systems, high-impact workflows, and the kind of engineering problems that actually stretch your skills.
  • Organization
    : Alignerr
  • Type
    : Hourly Contract
  • Location
    : Remote
  • Commitment
    : 20-40 hours/week
What You'll Do
  • Design, build, and optimize high-performance C# systems supporting AI data pipelines and evaluation workflows
  • Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control
  • Improve reliability, performance, and safety across existing C# codebases
  • Collaborate with data, research, and engineering teams to support model training and evaluation workflows
  • Identify bottlenecks and edge cases in data and system behavior, and implement scalable, production-ready fixes
  • Participate in synchronous design reviews and iterate on system architecture decisions with senior engineers
Who You Are
  • Native or fluent English speaker with clear written and verbal communication skills
  • Full-stack developer with a strong systems programming background
  • 3-5+ years of professional experience writing production-grade C#
  • Experienced in interoperability scenarios - such as invoking Python ML models from .NET or wrapping native libraries
  • Skilled at designing robust benchmarking and evaluation harnesses
  • Able to commit 20-40 hours per week consistently
Nice to Have
  • Prior experience with data annotation, data quality, or evaluation systems
  • Familiarity with AI/ML workflows, model training, or benchmarking pipelines
  • Experience with distributed systems or developer tooling
  • Background working directly with or alongside AI research teams
Why Join Us
  • Work on cutting-edge AI infrastructure alongside leading research labs
  • Fully remote and flexible - work from wherever you do your best engineering
  • Freelance autonomy with the structure and consistency of ongoing, meaningful project work
  • Tackle genuinely hard technical problems with real-world impact on AI systems at scale
  • Potential for ongoing work and contract extension as new projects launch