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Contract Data Annotation Jobs in Philadelphia, PA

... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ... Experience operating data contracts, lineage, and certification models in a regulated or quality ...

... annotation at enterprise scale. Responsible for * Certified, versioned data products and semantic ... Experience operating data contracts, lineage, and certification models in a regulated or quality ...

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Contract Data Annotation information

What is the difference between Contract Data Annotation vs Data Labeler?

AspectContract Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, project-basedRemote or on-site, task-based
Industry UsageAI/ML training, tech companiesAI/ML training, tech companies
Job FocusAnnotating data for machine learning modelsLabeling data to improve AI algorithms

Contract Data Annotation involves completing specific annotation projects for AI training, often on a contractual basis. Data Labelers focus on labeling data to enhance machine learning models, typically performing similar tasks. Both roles require attention to detail and are used in AI/ML industries, but Contract Data Annotation emphasizes project-based work with defined deliverables.

What is a contract data annotation job?

A contract data annotation job involves labeling or tagging data—such as images, text, audio, or video—according to specific guidelines, usually on a temporary or project-based contract. These annotations help train machine learning models by providing accurate, human-labeled examples for algorithms to learn from. Contract workers are typically hired for a set period or project and may work remotely or on-site, depending on the employer. The work requires attention to detail, adherence to quality standards, and sometimes familiarity with specialized annotation tools.

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

To thrive as a Contract Data Annotation Specialist, you need a keen eye for detail, strong analytical skills, and familiarity with data labeling standards, often supported by experience in data management or related fields. Proficiency with annotation platforms (such as Labelbox, Prodigy, or CVAT) and basic knowledge of data formats like JSON or XML are commonly required. Excellent communication, time management, and the ability to work independently help individuals excel in this often remote and deadline-driven role. These skills ensure high-quality, accurate data annotations that are vital for training reliable machine learning models.

What are some common challenges faced by contract data annotation professionals, and how can they be effectively managed?

Contract data annotation professionals often encounter challenges such as maintaining consistency in labeling, managing tight project deadlines, and ensuring data privacy. These challenges can be effectively managed by following detailed annotation guidelines, utilizing collaborative tools for team communication, and participating in regular quality assurance checks. Staying organized and proactive about seeking clarification from project leads also helps ensure high-quality, accurate results and a smooth workflow.
What are the most commonly searched types of Data Annotation jobs in Philadelphia, PA? The most popular types of Data Annotation jobs in Philadelphia, PA are:
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Head of Data Engineering, AI CoE

Agilent

Wilmington, DE • On-site

$171K - $321K/yr

Full-time

Posted 4 days ago


Agilent Technologies rating

8.2

Company rating: 8.2 out of 10

Based on 41 frontline employees who took The Breakroom Quiz

87th of 536 rated manufacturers


Job description

Job Description
Owns the Fabric data plane: the certified data and semantics every agent and BI use case depends on. The Agilent Intelligence Fabric is a single governed substrate serving both BI and agentic AI; one substrate, two consumption modes. This role makes the data side of that promise real, meaning every certified data product carries a semantic definition, a data contract, policy and entitlement metadata including agent identity, lineage and observability, and a certification tier.
The role operates on a core conviction of the program: AI is the primary builder of the Fabric, not merely its consumer. This leader deploys agents that generate metadata, resolve entities across domains, score quality, and classify unstructured content, so the data plane compounds in richness with every interaction rather than depending on manual annotation at enterprise scale.
Responsible for
  • Certified, versioned data products and semantic models, built in partnership with domain owners and stewards, with certification tiers that agents and BI consumers can both trust.
  • The Asset Registry, lineage, and data-quality signals; the registry is the discoverable, versioned home for data products and semantic definitions.
  • Lakehouse, vector, and graph retrieval foundations underpinning grounded agent behavior.
  • Agentic workloads that build the Fabric itself: metadata generation, entity resolution, quality scoring, and unstructured content classification.
  • Solid-line management of AI Data Engineers deployed into pods.
  • Leads a team responsible for designing, developing, and implementing modular data models, data pipelines, and data management frameworks that enable the capture, integration, storage, and utilization of structured and unstructured data from multiple sources.
  • Applies in-depth understanding of business and technical requirements to define data engineering priorities, direct the development of scalable data solutions, and establish standards and processes that ensure data reliability, efficiency, quality, compatibility, and accessibility.
  • Provides technical and organizational leadership in the development of data platforms and tools that support analytics, data science, predictive and prescriptive modeling, and automation initiatives, while overseeing project execution, cross-functional collaboration, talent development, and continuous improvement of data engineering capabilities to meet evolving business and product requirements.

Qualifications
  • Bachelor's or Master's Degree or equivalent. Plus, broad knowledge of functional area(s) of responsibility.
  • Minimum of 10 years' experience formally or informally leading people, projects and/or programs.
  • A track record building enterprise data platforms that serve production AI systems, not only analytics; experience with semantic layers, ontologies, or knowledge representation at scale.
  • Deep familiarity with the modern lakehouse, vector, and graph landscape; experience with Microsoft Fabric, Snowflake, or equivalent platforms in a multi-cloud estate.
  • Experience operating data contracts, lineage, and certification models in a regulated or quality-driven industry; life sciences or GxP exposure is a strong plus.
  • Curiosity about AI, its potential and its pitfalls. The field moves monthly, and the people who thrive here are genuinely curious about both sides of it: what these systems can newly do, and where they fail, mislead, or quietly degrade. We want people who read the failure analyses as eagerly as the launch posts, who experiment on their own initiative, and who hold excitement and skepticism at the same time without letting either one win permanently.
  • Lifelong learners. Whatever expertise a candidate arrives with will be partially obsolete within a year, and that is not a defect of the candidate; it is the condition of the field. We hire people who have reinvented their toolkit before and expect to do it again, who learn in public, and who treat being wrong as information rather than injury. A history of deliberate self-reinvention counts for more than any single credential.
  • Excellent communication and the ability to influence. Nothing in this organization ships by authority alone. Every role here persuades domain experts to engage, stewards to share what they know, sponsors to stay honest about value, and functions like Legal, Quality, and Security to move from gatekeeping to partnership. We look for people who write and speak clearly, who adapt their register from bench scientist to Board, and who change minds through credibility and clarity rather than escalation.
  • The instinct to automate curation with AI rather than scale it with headcount.

Additional Details
This job has a full time weekly schedule. Applications for this job will be accepted until at least August 3, 2026 or until the job is no longer posted.
The full-time equivalent pay range for this position is $171,600.00 - $321,750.00/yr plus eligibility for bonus, stock and benefits. Our pay ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. During the hiring process, a recruiter can share more about the specific pay range for a preferred location. Pay and benefit information by country are available at: https://careers.agilent.com/locations
Agilent Technologies, Inc. is an Equal Employment Opportunity and merit-based employer that values individuals of all backgrounds at all levels. All individuals, regardless of personal characteristics, are encouraged to apply. All qualified applicants will receive consideration for employment without regard to sex, pregnancy, race, religion or religious creed, color, gender, gender identity, gender expression, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, registered domestic partner status, age, sexual orientation, military or veteran status, protected veteran status, or any other basis protected by federal, state, local law, ordinance, or regulation and will not be discriminated against on these bases. Agilent Technologies, Inc., is committed to creating and maintaining an inclusive in the workplace where everyone is welcome, and strives to support candidates with disabilities. If you have a disability and need assistance with any part of the application or interview process or have questions about workplace accessibility, please email job_posting@agilent.com or contact +1-262-754-5030. For more information about equal employment opportunity protections, please visit www.agilent.com/en/accessibility.
Travel Required:
10% of the Time
Shift:
Day
Duration:
No End Date
Job Function:
Administration

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