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Data Annotation Manager Jobs in Secaucus, NJ (NOW HIRING)

Welocalize

Data Labeling Associate

New York, NY

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

Welocalize

Data Labeling Associate

New York, NY

$34/hr

WHAT YOU'LL DO • Execute Data labelling and annotation tasks across speech and voice datasets. • Work with audio and language data, including transcription, categorization, and tagging. YOU ARE A ...

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All JobsData Annotation JobsData Annotation Manager JobsData Annotation Manager Jobs in Secaucus, NJ

Data Annotation Manager information

See Secaucus, NJ salary details

$31.5K

$98.8K

$174.9K

How much do data annotation manager jobs pay per year?

As of Jun 14, 2026, the average yearly pay for data annotation manager in Secaucus, NJ is $98,765.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,100.00 and $127,600.00 per year, depending on experience, location, and employer.

What is the salary of data annotation manager?

The salary of a Data Annotation Manager typically ranges from $60,000 to $120,000 annually, depending on experience, location, and company size. Senior roles or those in high-cost areas may offer higher compensation, and proficiency with annotation tools and team management can influence pay levels.

Is data annotation high paying?

Data annotation managers typically earn higher salaries than entry-level annotators due to their supervisory responsibilities and expertise in labeling tools and processes. Salaries vary based on experience, location, and company size, but the role generally offers competitive pay within the data labeling industry.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation managers oversee this work, ensuring accuracy and quality using tools like labeling platforms and quality control procedures.

What are some common challenges faced by Data Annotation Managers, and how can they be addressed?

Data Annotation Managers often encounter challenges such as maintaining high annotation quality across large and diverse datasets, managing a distributed team of annotators, and meeting tight project deadlines. To address these, it's important to implement robust quality assurance processes, provide ongoing training for annotators, and establish clear communication channels. Leveraging annotation tools with built-in validation features can also help ensure consistency and accuracy. Building a positive and collaborative team environment further contributes to better outcomes and workflow efficiency.

What does a Data Annotation Manager do?

A Data Annotation Manager oversees the process of labeling and categorizing data used to train machine learning models. They manage teams of annotators, ensure data quality, develop annotation guidelines, and coordinate with data scientists to meet project requirements. Their role is critical in maintaining high standards of accuracy and efficiency, as well as ensuring that datasets are properly prepared for AI and machine learning applications.

Is it hard to get a job with data annotation?

Securing a job as a data annotation manager typically requires experience in data labeling, familiarity with annotation tools, and understanding of data quality standards. While entry-level roles may be accessible with basic skills, advancing to managerial positions often demands relevant experience and leadership abilities.

What are the key skills and qualifications needed to thrive as a Data Annotation Manager, and why are they important?

To thrive as a Data Annotation Manager, you need expertise in data labeling processes, quality control, and a solid understanding of machine learning concepts, usually backed by a degree in computer science or a related field. Proficiency with annotation tools such as Labelbox, Supervisely, or CVAT, as well as experience with project management systems, is commonly required. Exceptional leadership, attention to detail, and strong communication skills help manage teams and ensure high annotation accuracy. These skills are critical for delivering reliable labeled datasets, which are essential for building effective AI and machine learning models.

What is the difference between Data Annotation Manager vs Data Labeling Specialist?

AspectData Annotation ManagerData Labeling Specialist
CredentialsBachelor's degree in related field, experience in data managementHigh school diploma or equivalent, training in labeling tools
Work EnvironmentTeam management, project oversight, collaboration with data scientistsHands-on labeling work, using annotation tools, focused on data tagging
Industry UsageUsed in AI/ML projects for overseeing annotation teamsPerforms the actual data labeling tasks in machine learning workflows

The Data Annotation Manager oversees the entire annotation process, managing teams and ensuring quality, while the Data Labeling Specialist focuses on executing labeling tasks. Both roles are essential in AI/ML data preparation but differ in responsibilities and scope.

What are the most commonly searched types of Data Annotation jobs in Secaucus, NJ? The most popular types of Data Annotation jobs in Secaucus, NJ are:
What job categories do people searching Data Annotation Manager jobs in Secaucus, NJ look for? The top searched job categories for Data Annotation Manager jobs in Secaucus, NJ are:
What cities near Secaucus, NJ are hiring for Data Annotation Manager jobs? Cities near Secaucus, NJ with the most Data Annotation Manager job openings:
Data Annotation Manager jobs near you
Infographic showing various Data Annotation Manager job openings in Secaucus, NJ as of June 2026, with employment types broken down into 100% Full Time. Highlights an 74% In-person, and 26% Remote job distribution, with an average salary of $98,765 per year, or $47.5 per hour.
Technical GTM Manager, Data Licensing & AI Services

Technical GTM Manager, Data Licensing & AI Services

Shutterstock

New York, NY • On-site

Full-time

Posted 15 days ago

Job description

The Opportunity

Shutterstock's Data Licensing and AI Services division helps AI model builders source, license, curate, and evaluate high-quality creative datasets for training, fine-tuning, and improving multimodal AI systems.

We are seeking a Technical GTM Manager to join Shutterstock's Data Licensing and AI Services team. This role sits at the intersection of product marketing, technical positioning, sales enablement, and market intelligence for AI training data.

The right candidate will be excited by questions like: How do AI teams decide what data to buy? What makes a dataset useful for training or evaluation? How do metadata, QA, rights, provenance, and expert judgment create customer value?

Shutterstock already works with leading AI companies and brings together rights-cleared creative assets, creator relationships, custom production capabilities, metadata expertise, data partnerships, and operational rigor. Your role will be to translate those strengths into clear positioning, sales narratives, and go-to-market materials for model-training customers.

This role reports into the Product Marketing team in Shutterstock's Data Licensing and AI Services division.

What You'll Do
  • Develop positioning and messaging for Shutterstock's AI training data offerings, including licensed datasets, custom data solutions, metadata enrichment, expert-informed data, and partner-sourced supply.
  • Translate technical product value into buyer-facing narratives for AI labs, model builders, data procurement teams, research teams, product teams, and strategic partnerships teams.
  • Create sales enablement materials, including pitch decks, one-pagers, objection-handling guides, product explainers, customer proof points, and internal training materials.
  • Track the AI training data ecosystem, including data providers, evaluation companies, labeling platforms, dataset marketplaces, content licensors, synthetic data companies, and multimodal AI companies.
  • Research how AI teams procure data, evaluate vendors, compare datasets, assess rights and provenance, define quality requirements, and justify spend.
  • Partner with Product, Sales, Data Partnerships, Studios, Legal, Metadata, Operations, Engineering, and Marketing to turn complex capabilities into market-ready offerings.
What You'll Bring
  • 3+ years of experience in product marketing, technical marketing, go-to-market strategy, product strategy, business development, partnerships, consulting, customer solutions, research operations, or another relevant B2B role.
  • Demonstrated interest in AI, machine learning, model training, data products, model evaluation, creative AI, or AI infrastructure.
  • Ability to understand technical concepts and translate them into clear positioning, messaging, and sales narratives.
  • Familiarity with some of the following: model training, fine-tuning, evaluation, dataset quality, metadata, annotation, data labeling, data procurement, data partnerships, synthetic data, or multimodal AI.
  • Strong writing skills, especially for technical or semi-technical audiences.
  • Comfort operating in an ambiguous, fast-moving market where product categories are still being defined.
  • Ability to work cross-functionally with sales, product, engineering, legal, operations, marketing, and creative production teams.
Strong Plus
  • Experience at or around an AI lab, AI data provider, data labeling company, model evaluation company, data marketplace, ML infrastructure company, creative AI company, or technical marketplace.
  • Experience with multimodal AI, image/video/audio datasets, computer vision, generative AI, or human-in-the-loop data workflows.
  • Experience marketing or selling to technical buyers such as ML teams, research teams, data procurement teams, data partnerships teams, AI product teams, or engineering organizations.
  • Experience with dataset documentation, metadata schemas, QA workflows, annotation guidelines, rights/provenance documentation, data delivery specs, or model evaluation workflows.
Why Shutterstock:

  • You have a direct impact on the success of the company. Your work matters and is essential to the evolution of our growing AI Business

  • Executive leadership cares personally. They prioritize growth and planning your career path with your goals and passions in mind.

  • Flexibility to work between home and office with everything you need to be successful in both

  • A generous and competitive benefits package.

Shutterstock connects diverse artists and creative professionals around the globe with the agencies, brands and people who need their work and services. It's a place where creators come to be inspired and discover new ways to produce their best work.

Shutterstock enables its employees to drive culture and tap into the world around them to develop the toolbox and solutions that help others share their world views. At Shutterstock, your ideas will be welcomed, your uniqueness will be celebrated, and you will be supported in presenting your view of the world as you experience it. We're champions of resiliency; quickly learning from our shortcomings in our pursuit of continuous growth.

Diverse teams are critical to our success. We encourage people from different backgrounds to apply and we commit to creating and maintaining a culture where employees know they belong and have equal opportunities to succeed.

#LI-Hybrid

#LI-MS1

    At Shutterstock, we are committed to providing competitive pay and benefits that are in line with industry standards. The compensation package offered may vary depending on employment experience, skills, and knowledge. You may also be eligible for our generous benefits package including health, wellness and financial benefits. Compensation ranges for candidates in locations outside of the location(s) below may differ based on the cost of labor, market, and additional factors.
    The pay range for this position is below:

    130,000 - 150,000 per year in New York

    Note: Commission-eligible roles are expressed as on-target earnings (base and commission). Non-commission roles are expressed as base salary only but are also eligible for annual incentives.

    Shutterstock Values

    We are one team collectively focused on creating an unrivaled experience for our Customers and Contributors. Our Values represent the mindset of the employee who will thrive at Shutterstock. If you are passionate about what you do, and want to become part of a cutting-edge technology company building industry leading products, please apply.

    Shutterstock is an Equal Opportunity Employer. Suitably qualified and eligible candidates are encouraged to apply regardless of age, color, disability, national origin, ancestry, race, religion, gender, sexual orientation, gender identity and/or expression, veteran status, genetic information, or any other status protected by applicable law.
    Shutterstock ensures that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Persons with disabilities who anticipate needing accommodations for any part of the application process may contact, in confidence,accommodation_request@shutterstock.com.

    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.

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