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Data Annotation Jobs in Wheat Ridge, CO (NOW HIRING)

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Data Annotation information

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.

Is data annotation a genuine job?

Data annotation is a legitimate job that involves labeling data such as images, text, or audio to help train machine learning models. It often requires attention to detail and familiarity with annotation tools, and can be found in various industries like technology and healthcare.

Does data annotation pay well?

Data annotation jobs typically offer entry-level pay that varies depending on the employer, location, and complexity of the tasks. While some positions pay hourly wages comparable to other administrative or clerical roles, experienced annotators working on specialized projects or with advanced tools can earn higher rates. Overall, data annotation is often considered an entry-level position with moderate pay potential.

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.

How hard is it to get hired by data annotation?

Getting hired for a data annotation role generally requires basic computer skills, attention to detail, and sometimes familiarity with specific tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible, though competition can vary based on the employer and location.

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.
What job categories do people searching Data Annotation jobs in Wheat Ridge, CO look for? The top searched job categories for Data Annotation jobs in Wheat Ridge, CO are:
What cities near Wheat Ridge, CO are hiring for Data Annotation jobs? Cities near Wheat Ridge, CO with the most Data Annotation job openings:
Data Annotation jobs near you
Infographic showing various Data Annotation job openings in Wheat Ridge, CO as of June 2026, with employment types broken down into 3% As Needed, 53% Full Time, 38% Part Time, and 6% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Principal Python Engineer - ML Infrastructure

Alignerr

Denver, CO • On-site

Other

Posted 5 days ago

Job description

Principal Python Engineer - ML Infrastructure (AI Training)
About the Role
What if your Python expertise could directly shape the infrastructure powering some of the world's most advanced AI systems? We're looking for a Principal Python Engineer to build and optimize the data pipelines, annotation tooling, and evaluation systems that leading AI labs depend on - working on real production code with meaningful, measurable impact.
This is a fully remote, flexible contract role for a senior engineer who thrives at the intersection of systems programming, distributed computing, and AI infrastructure.
  • 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 large-scale AI data pipelines and model evaluation workflows
  • Develop full-stack backend tooling and services for data annotation, validation, and quality control at scale
  • Diagnose and resolve bottlenecks across compute-heavy, distributed systems using advanced async patterns and profiling techniques
  • Improve reliability, safety, and performance across existing production Python codebases
  • Collaborate closely with data, research, and engineering teams to accelerate model training and evaluation cycles
  • Drive architectural decisions through synchronous design reviews and clear technical communication
Who You Are
  • 5+ years writing production Python for large-scale infrastructure or platform engineering
  • Deep expertise in distributed computing, concurrency, and advanced asynchronous programming patterns
  • Fluent in Python internals - including GIL limitations, memory profiling, and performance optimization for compute-heavy workloads
  • Experienced full-stack developer with a strong systems programming background
  • Clear, confident communicator capable of driving technical strategy and architectural decisions
  • Native or fluent English speaker
  • Available to commit 20-40 hours per week
Nice to Have
  • Prior experience with data annotation, data quality, or evaluation systems
  • Familiarity with AI/ML workflows, model training, or benchmarking pipelines
  • Background in distributed systems architecture or developer tooling
  • Exposure to working directly with AI research teams or labs
Why Join Us
  • Work on real, high-impact production systems used by leading AI research labs
  • Fully remote and flexible - work when and where it suits you
  • Freelance autonomy with the depth and structure of meaningful, long-term technical work
  • Collaborate with top engineers and researchers at the frontier of AI development
  • Potential for ongoing work and contract extension as new projects launch

Apply