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Overnight Data Annotation Specialist Jobs (NOW HIRING)

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Overnight Data Annotation Specialist information

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$28K

$72.9K

$88K

How much do overnight data annotation specialist jobs pay per year?

As of Aug 22, 2026, the average yearly pay for overnight data annotation specialist in the United States is $72,947.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,000.00 and $87,000.00 per year, depending on experience, location, and employer.

What is an overnight data annotation specialist?

Overnight Data Annotation Specialists are professionals who label, categorize, and annotate data—such as images, text, or audio—during overnight hours to support machine learning and artificial intelligence projects. Their work ensures that data used to train AI models is accurate and well-organized, which helps improve algorithms’ performance. These specialists may work remotely or onsite, often for companies that require round-the-clock data processing. The overnight schedule is ideal for organizations operating across global time zones or needing continuous project progress.

What are the key skills and qualifications needed to thrive as an overnight data annotation specialist?

To thrive as an Overnight Data Annotation Specialist, you typically need attention to detail, accuracy, and a strong understanding of data labeling protocols, often supported by a high school diploma or relevant experience. Familiarity with data annotation platforms, spreadsheets, and content management systems is commonly required, and some employers may request basic programming or machine learning knowledge. Strong time management, self-motivation, and the ability to work independently during overnight hours are standout soft skills for this role. These competencies ensure high-quality, consistent data labeling that is critical for training reliable machine learning models and supporting data-driven projects.

What are the typical challenges faced by an overnight data annotation specialist, and how can they be managed?

Overnight Data Annotation Specialists often face challenges such as maintaining focus during late hours, managing fatigue, and ensuring high accuracy in repetitive tasks. Working overnight can disrupt regular sleep patterns, so it's important to establish a consistent sleep schedule and take short, scheduled breaks to stay alert. Additionally, clear communication with the team—often through digital channels—is key, as many colleagues may work during daytime hours. Developing strong self-management skills and using productivity tools can help maintain annotation quality and meet deadlines.

What is the difference between Overnight Data Annotation Specialist vs Data Labeling Technician?

AspectOvernight Data Annotation SpecialistData Labeling Technician
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or office, overnight shiftsRemote or on-site, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Search IntentComparison of roles in data annotationComparison of roles in data labeling

The Overnight Data Annotation Specialist and Data Labeling Technician roles both involve preparing data for AI models, often requiring similar skills and industry usage. The main difference lies in shift timing, with the specialist working overnight shifts, often remotely, focusing on detailed annotation tasks. The technician may work flexible hours and handle broader labeling tasks. Both roles are essential in AI data pipelines, but the specialist's overnight schedule distinguishes it from the more flexible technician position.

What cities are hiring for Overnight Data Annotation Specialist jobs?

Cities with the most Overnight Data Annotation Specialist job openings:

What are the most commonly searched types of Data Annotation Specialist jobs?

The most popular types of Data Annotation Specialist jobs are:

What states have the most Overnight Data Annotation Specialist jobs?

States with the most job openings for Overnight Data Annotation Specialist jobs include:

Infographic showing various Overnight Data Annotation Specialist job openings in the United States as of July 2026, with employment types broken down into 2% Locum Tenens, 19% Full Time, 17% Part Time, 19% Contract, 42% Nights, and 1% Summer. Highlights an 34% Physical, and 66% Remote job distribution, with an average salary of $72,947 per year, or $35.1 per hour.

Data Annotator / Geospatial Annotation Specialist

Aechelon Technology

South San Francisco, CA

$82K - $92K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted 2 days ago


Job description

The Data Annotator / Geospatial Annotation Specialist plays a critical role in the creation of high-quality training datasets used to develop and refine Aechelon's machine learning and computer vision models. This role supports both the Advanced Model Development Group and the Applied Real-Time Vision Group, ensuring datasets for object detection, segmentation, and classification are accurate, consistent, and production-ready.
The Specialist performs detailed vector annotation, image segmentation, and dataset preparation while adhering to strict quality standards. Because model performance is highly dependent on high-quality annotation, this role requires exceptional attention to detail and a strong understanding of geospatial imagery.
In addition to dataset creation, the Specialist will learn core machine learning concepts and gain experience operating inference tools and models within the DAML pipeline, becoming a direct contributor to model evaluation and workflow improvements.


Key Responsibilities
  • Create precise vector annotations and segmentation masks for training computer vision and object detection models.
  • Perform detailed image segmentation, manually labeling features across large and varied imagery datasets.
  • Follow established annotation guidelines and maintain consistency across global AOIs.
  • Validate and refine automated detection outputs; correct errors or incomplete detections.
  • Work with ML team to understand annotation needs, edge cases, and quality thresholds.
  • Learn how to operate model inference tools and assist in evaluating model performance.
  • Provide feedback on false positives/negatives, detection weaknesses, and annotation ambiguities.
  • Maintain structured documentation of annotation processes, datasets, feature definitions, and QA results.
  • Support improvements to dataset pipelines and annotation workflows through iterative refinement and testing.
  • Assist multiple DAML groups as needed, depending on dataset demands and model development cycles.
Required Qualifications
  • Background in GIS, Remote Sensing, Image Analysis, Digital Art, Photography, or related field (degree preferred but not required with strong experience).
  • Prior experience with image annotation, data labeling, GIS feature extraction, or segmentation workflows.
  • Ability to visually identify subtle features in imagery with extreme precision.
  • Strong analytical, organizational, and documentation skills.
  • Ability to work with large datasets for extended periods while maintaining accuracy and focus.
Required Skills and Tools
  • Adobe Photoshop (Advanced): Expertise in mask creation, polygon tracing, color differentiation, clean-up workflows, and segmentation editing.
  • GIS Tools (Intermediate+): Ability to work in QGIS, ERDAS Imagine, or Global Mapper for spatial visualization and annotation support.
  • Geospatial Data Handling: Ability to work with shapefiles, GeoPackages, raster datasets, and other formats used in ML workflows.
  • Python (Basic-Intermediate): Ability to run scripts, perform data checks, and assist with pre-processing tasks.
  • Documentation Tools: Proficiency using Jupyter Notebook and Git for tracking annotation notes and revisions.
Strongly Desired Skills and Tools
  • Experience creating training datasets for machine learning, object detection, or image segmentation models.
  • Familiarity with YOLO, PyTorch, or fast.ai (conceptual knowledge acceptable).
  • Ability to create simple scripts to automate annotation steps or pre-processing tasks.
  • Experience using ChatGPT or other LLMs to improve workflows, generate helper scripts, or automate documentation.
  • Understanding of geospatial features such as vegetation, buildings, vehicles, aircraft, or other runtime elements.
Reporting Expectations

The Specialist reports jointly to managers in the Advanced Model Development and Applied Real-Time Vision groups depending on project assignment. Regular updates are expected on dataset progress, annotation quality, workflow blockers, and model evaluation findings. The Specialist is expected to meet annotation quotas while maintaining strict accuracy and quality standards.


Compensation

$82,000 - 92,000 / year 

The above range is specific to CALIFORNIA and may not be applicable to other locations. Final compensation is based on factors such as the candidate's skills, qualifications, and experience. 

 We offer a very attractive compensation package including competitive base salary, company performance-based profit sharing, 401k, 100% employer paid health benefits (medical, dental, vision, life, std, ltd, and life insurance plans). 

No relocation reimbursement provided.