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Contract Data Annotation Jobs (NOW HIRING)

Alignerr

Data Platform Engineer (Python)

Manhattan, NY · Remote

... annotation tooling, and evaluation systems that leading AI labs depend on to train and improve ... This is a fully remote contract role working on real production systems - not toy projects. You'll ...

Alignerr

C# Infrastructure Engineer - Data Pipelines

Seattle, WA · Remote

$122.40K - $160.60K/yr

... annotation tooling, and evaluation systems that sit at the heart of cutting-edge AI development ... This is a fully remote, flexible contract role working alongside leading AI labs on real production ...

Crossing Hurdles

Attorney | Remote

Manhattan, NY · Remote

Perform simulated contract negotiations and redlining for SaaS agreements. Evaluate AI-generated ... Interest in legal technology, AI, and data annotation workflows. #J-18808-Ljbffr

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Contract Data Annotation information

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 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 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.

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Contract Data Annotation jobs near you
Infographic showing various Contract Data Annotation job openings in the United States as of May 2026, with employment types broken down into 98% Full Time, and 2% Contract. Highlights an 46% Physical, 1% Hybrid, and 53% Remote job distribution.

Data Platform Engineer (Python)

Alignerr

Seattle, WA • Remote

Full-time

Posted 28 days ago

Job description

Data Platform Engineer (Python) About the Role What if your Python expertise could directly shape the infrastructure that trains and evaluates the most advanced AI systems in the world? We're looking for a Senior Python Full-Stack Engineer to design and build the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on. This is a fully remote, flexible contract role for an experienced engineer who thrives on high-impact, technically challenging work. If you've spent years building production Python systems and want to apply that experience at the frontier of AI development - this is the role.
  • Organization : Alignerr
  • Type : Hourly Contract
  • Location : Remote
  • Commitment : 20-40 hours/week
What You'll Do
  • Design, build, and optimize high-performance Python 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 Python 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 to iterate on system architecture and implementation decisions
Who You Are
  • Native or fluent English speaker with clear written and verbal communication skills
  • Full-stack developer with a strong systems programming background
  • 5+ years of professional experience writing production Python for data engineering
  • Proficient with workflow orchestration tools to manage complex dependency graphs
  • Experienced with dataframe processing libraries and cloud data warehouse SDKs in Python
  • Self-directed and reliable - able to commit 20-40 hours per week and deliver consistently
Nice to Have
  • Prior experience with data annotation, data quality, or model evaluation systems
  • Familiarity with AI/ML workflows, model training pipelines, or benchmarking infrastructure
  • Experience with distributed systems or developer tooling
  • Background working with or alongside AI research teams
Why Join Us
  • Work on real production systems used by leading AI research labs
  • Fully remote and async-friendly - work from wherever you do your best work
  • Freelance autonomy with the structure and consistency of ongoing project-based work
  • Make a tangible impact on the infrastructure powering next-generation AI models
  • Potential for extended engagement and additional projects as the work evolves

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