Company Description
Atlas Capture is at the forefront of innovation, building the foundational data layer for Physical AI. Our data platform powers frontier Physical AI models how to perceive, reason, and act in the real world. Atlas Capture is dedicated to advancing technology and empowering businesses and industries with cutting-edge AI-driven solutions. Joining the team means being part of a mission to shape the future of Physical AI and intelligent systems.
As a Data Annotator, you will play a critical role in creating high-quality labeled datasets that power Physical AI models. You will perform detailed annotation across video, image, and multimodal data, following precise guidelines to ensure accuracy, consistency, and reliability. Your work will directly influence model performance and real-world AI behavior.
This role requires strong English proficiency and candidates 18 years of age or older.
What You Will Do
High-Quality Data Annotation
- Perform annotation and labeling tasks across video, image, and multimodal data.
- Accurately apply English-language annotation guidelines to complex, real-world scenarios.
- Maintain high standards of consistency, precision, and attention to detail.
- Identify edge cases and ambiguous examples, escalating questions clearly and concisely in English.
Quality & Consistency
- Meet or exceed quality benchmarks for accuracy and completeness.
- Self-review work to catch errors and maintain consistency.
- Apply feedback from QA reviewers and team leads to improve annotation quality.
- Follow annotation standards, workflows, and quality requirements exactly as written.
Workflow Execution
- Complete assigned annotation tasks within expected throughput and turnaround times.
- Follow established processes for task tracking, documentation, and submission.
- Use annotation tools and platforms efficiently.
- Maintain strict confidentiality and comply with all data security and privacy requirements.
Collaboration & Communication
- Communicate clearly and professionally in English with team leads, QA, and peers.
- Participate in English-language training sessions, calibrations, and guideline updates.
- Ask precise questions and provide feedback when instructions or edge cases are unclear.
Qualifications
Required
- Must be 18 years of age or older.
- Fluent or highly proficient in spoken and written English.
- Prior experience in data annotation, labeling, content review, or quality-focused work.
- Strong attention to detail and ability to follow complex English-language instructions.
- Ability to perform repetitive, high-precision tasks with sustained focus.
- Comfort using web-based tools and annotation platforms.
- Clear written communication skills for documenting issues and asking questions in English.
Nice to Have
- Experience annotating video, image, or multimodal datasets for ML or AI applications.
- Familiarity with annotation tools or labeling platforms.
- Experience working with remote or distributed teams.
- Exposure to quality control or calibration workflows.
- Additional language proficiency beyond English.
