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Data Annotation Engineer Jobs in New York, NY (NOW HIRING)

Distyl AI

Research Engineers, Data

New York, NY · On-site

$150K - $250K/yr

Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in ... Strong Data Engineering Fundamentals: You write clean Python and SQL, understand data modeling and ...

Meta

Sourcing Manager, Data Operations

New York, NY · Remote

$139K/yr

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration ... Experience in managing high-volume data annotation sourcing programs * Demonstrated ability to ...

Meta

Sourcing Manager, Data Operations

New York, NY · On-site

$139K - $196K/yr

... AI data annotation and collection vendors • Proactively identify, track, and manage risks and ... g., prompt/context engineering, agent orchestration) and staying current with emerging AI ...

Socket.dev

Research Engineers, Data

Manhattan, NY · On-site

$150 - $250/hr

Develop synthetic data, annotation, and feedback‑loop strategies to improve system performance in ... Strong Data Engineering Fundamentals: You write clean Python and SQL, understand data modeling and ...

Mecka

Human Data Architect, Quality

Manhattan, NY · On-site

$130 - $160/hr

Partner with engineering on automated validation (schema completeness, duplicates, time sync ... Who You Are Required Background * 5+ years working at the intersection of ML and data -- annotation ...

JPMorgan Chase & Co.

Software Engineer II

Jersey City, NJ · On-site

$106K - $146K/yr

Design and deliver services for data preparation, annotation workflows, lineage, and auditability * Develop cloud-native microservices and application programming interfaces to support scalable model ...

New

The Consensus

Human Data Architect, Quality

Manhattan, NY · On-site

$140 - $190/hr

Partner with engineering on automated validation (schema completeness, duplicates, time sync ... Who You Are Required Background * 5+ years working at the intersection of ML and data -- annotation ...

JPMorgan Chase & Co

Software Engineer II

Jersey City, NJ · On-site

$106K - $146K/yr

Design and deliver services for data preparation, annotation workflows, lineage, and auditability * Develop cloud-native microservices and application programming interfaces to support scalable model ...

New

JP Morgan Chase

Software Engineer II

Jersey City, NJ · On-site

$106K - $146K/yr

Design and deliver services for data preparation, annotation workflows, lineage, and auditability * Develop cloud-native microservices and application programming interfaces to support scalable model ...

New

NBCUniversal

Senior Data Scientist

Manhattan, NY

$120K - $150K/yr

Work with partner ML and Annotation engineers and TPMs to spec out data and training requirements. * Data Strategy & Pipeline Oversight: Ensure that datasets are correctly curated, filtered, and ...

NBCUniversal

Senior Data Scientist

Manhattan, NY · On-site

$120K - $150K/yr

Work with partner ML and Annotation engineers and TPMs to spec out data and training requirements. * Data Strategy & Pipeline Oversight: Ensure that datasets are correctly curated, filtered, and ...

NBCUniversal

Senior Data Scientist

Manhattan, NY · On-site

$120K - $150K/yr

Work with partner ML and Annotation engineers and TPMs to spec out data and training requirements. * Data Strategy & Pipeline Oversight: Ensure that datasets are correctly curated, filtered, and ...

YO AI Labs

AI Consulting Expert - Remote

New York, NY · Remote

$100 - $200/hr

Prompt Engineering * AI Output Evaluation * Quality Assurance * Technical & Report Writing * Business Communication * Content Review & Editing * Data Interpretation * Data Annotation * Fact Checking

Latent

Clinical Informatics Specialist

New York, NY · On-site

$75K - $100K/yr

The Clinical Specialist will play a critical role in data generation, annotation, and evaluation to ... You will partner closely with product managers, engineers, and data scientists to ensure Latent ...

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Showing results 21-40

All JobsData Annotation Engineer JobsData Annotation Engineer Jobs in New York, NY

Data Annotation Engineer information

See New York, NY salary details

$56.3K

$161.3K

$215.5K

How much do data annotation engineer jobs pay per year?

As of Sep 6, 2026, the average yearly pay for data annotation engineer in New York, NY is $161,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,900.00 and $214,400.00 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 York, NY?

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

What job categories do people searching Data Annotation Engineer jobs in New York, NY look for?

The top searched job categories for Data Annotation Engineer jobs in New York, NY are:

What cities near New York, NY are hiring for Data Annotation Engineer jobs?

Cities near New York, NY with the most Data Annotation Engineer job openings:

Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in New York, NY as of August 2026, with employment types broken down into 1% As Needed, 85% Full Time, 11% Part Time, and 3% Contract. Highlights an 84% Physical, 4% Hybrid, and 12% Remote job distribution, with an average salary of $162,561 per year, or $78.2 per hour.

Research Engineers, Data

Distyl AI

New York, NY • On-site

$150K - $250K/yr

Full-time

Medical, Dental, Vision, Retirement

Posted 9 days ago

Key responsibilities

  • Design and build data systems that power reliable AI workflows across enterprise environments

  • Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific data used by AI systems

  • Create data quality frameworks that identify coverage gaps, ambiguity, drift, duplication, leakage, and other failure modes

Job description

About Distyl AI
Distyl is an applied AI technology company partnering with the world's most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.
We research and deploy technologies that power AI-native operations - both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations - from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys.
Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s.
What We Are Looking For
At Distyl, Research Engineers build the bridge between frontier AI research and production systems that deliver real business value. This role is for engineers who are excited to investigate how AI systems should be designed, rapidly prototype new ideas, and turn promising concepts into reliable systems that work inside real customer environments.
Research Engineers operate at the intersection of applied research, systems engineering, and customer-facing deployment. They design and implement compound AI systems, run experiments to understand system behavior, build evaluation frameworks, and collaborate closely with AI Researchers, AI Engineers, and customer stakeholders. Their work is not limited to demos or isolated prototypes: they help turn new techniques into robust systems that can be measured, operated, and improved in production.
Key Responsibilities
  • Design and build data systems that power reliable AI workflows across enterprise environments
  • Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific data used by AI systems
  • Create data quality frameworks that identify coverage gaps, ambiguity, drift, duplication, leakage, and other failure modes
  • Build tools and workflows that help teams turn raw customer data into usable context for retrieval, evaluation, reasoning, and execution
  • Partner with AI Researchers and AI Engineers to understand how data quality affects system behavior and production outcomes
  • Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in areas where real-world data is sparse or noisy
  • Analyze customer workflows and datasets to determine what information AI systems need, where that information should come from, and how it should be represented
  • Communicate clearly with internal teams and customer stakeholders about data assumptions, limitations, risks, and tradeoffs

Who You Are
  • Experience Building Data Systems for AI: You have built data pipelines, evaluation datasets, labeling workflows, retrieval corpora, or similar systems that improve model or agent behavior
  • Strong Data Engineering Fundamentals: You write clean Python and SQL, understand data modeling and pipeline reliability, and can build systems that are maintainable under production constraints
  • Research-Oriented Builder: You are comfortable investigating how data quality, structure, and representation affect AI system performance
  • AI-Native Working Style: You use AI tools daily to accelerate coding, analysis, debugging, exploration, and workflow automation
  • Comfort with Ambiguous Data: You can reason through messy enterprise datasets, incomplete documentation, conflicting business definitions, and changing requirements
  • Bias Towards Measurement: You prefer to make data quality and system behavior observable through concrete metrics, evaluations, and experiments
  • Customer Environment Readiness: You can work directly with customer teams to understand their data, ask precise questions, and explain tradeoffs clearly
  • Ownership Mentality: You take responsibility for whether the data layer enables the AI system to deliver reliable value in production

What We Offer
  • The base salary range for this role is $150K - $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
  • 100% coverage of medical, dental, and vision insurance for employee and dependents
  • Flexible time off
  • Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources
  • Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot
  • Complimentary in-office lunches and snacks provided
  • Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems
  • Ownership of high-impact projects across top enterprises
  • A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday-Thursday) in‑office.
#LI-Hybrid
We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.

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