Data Annotation Analyst – AI Perception Career at Appen

Appen Limited; United States; Remote; USD 40,000 - 65,000; Full time

Job summary

Appen Limited is seeking a Data Annotation Analyst for its remote US-based team. The role focuses on labeling camera imagery, video sequences, and LiDAR data to support perception models for autonomous machines.

You will follow strict specifications while balancing accuracy and production volume. Ideal candidates are detail-oriented with strong spatial reasoning and experience with image annotation workflows.

Qualifications

• High attention to detail to maintain accuracy for complex visual data.
• Strong spatial reasoning to interpret 3D environments and object pose.
• Experience with image/video annotation workflows and dedicated annotation tools.

Responsibilities

• Annotate 2D and 3D objects in images, video, and LiDAR data.
• Create and maintain segmentation, object tracking, and keypoint annotations.
• Follow detailed guidelines to ensure consistency and quality in large datasets.
• Review QA feedback and contribute to guideline improvements.
• Document data quality issues with clear steps for reproduction.
• Engage in calibration sessions and team standups to align interpretations.

Skills

Attention to detail

Spatial reasoning

Repetitive task handling

Education

Associate or bachelor's degree

Tools

Annotation tools

Job description

Data Annotation Analyst – AI Perception Career at Appen — Remote

Career Positioning: Data annotation is the foundational layer of modern AI — and Appen has been a dominant player for 30 years. Working here gives you direct exposure to LiDAR, computer vision, and autonomous systems pipelines, which are among the fastest-growing areas in AI. These skills transfer well into roles like ML Data Engineer, Perception QA Engineer, or AI Trainer at robotics and autonomous vehicle companies.

Compensation Benchmarks: No salary is disclosed, which is a mild red flag. Data annotation analyst roles in the US typically range from $40,000–$65,000 annually at this level. Appen historically offers contract-to-hire or hourly structures for annotation roles — worth clarifying before accepting an offer.

Green Flags:

• Exposure to cutting-edge perception model development for autonomous machinery — a high-demand, fast-growing niche.


• Appen's global scale (1M+ contributors, 200+ countries) means strong institutional processes and career infrastructure.


• The role explicitly values guideline improvement and edge-case documentation — signals upward mobility into QA Lead or Labeling Ops roles.

Yellow Flags:

• Repetitive, production-volume work can limit creative growth if you don't actively pursue advancement.


• No salary transparency is disclosed in the posting.


• The company-provisioned machine requirement suggests tight operational controls.

Best suited for: Early-career professionals targeting AI/ML ops, or career-changers from GIS, surveying, or construction looking to pivot into the AI industry.

About the Role

We're building high-quality ground-truth datasets used to train and validate perception models for autonomous and operator-assisted machines working in complex, real-world environments.

As a Data Annotation Analyst, you'll work with camera imagery, video, and LiDAR point clouds to create precise labels that help perception systems understand objects, people, terrain, and surrounding environments. You'll work in specialized annotation tools, following detailed specifications while balancing accuracy, consistency, and production volume.

Your Impact

• Annotate 2D and 3D objects across images, video, and LiDAR point clouds, including vehicles, machinery, people, signage, and environmental features.


• Create and maintain accurate segmentation, object tracking, pose, and keypoint annotations across sequences.


• Apply detailed annotation guidelines, including class definitions, occlusion rules, object thresholds, and inclusion/exclusion criteria.


• Review your work, respond to QA feedback, and maintain established quality and accuracy standards.


• Identify and elevate ambiguous scenes, sensor artifacts, tooling issues, and gaps in specifications rather than making assumptions.


• Document data quality and tooling issues with clear details and reproduction steps.


• Participate in calibration sessions, guideline reviews, and team standups to maintain consistent interpretations.


• Share observations that help improve annotation guidelines, taxonomies, and edge-case documentation.

Success in this role means producing accurate, consistent annotations at the expected volume while helping maintain a reliable, high-quality dataset.

What You Bring

• Strong attention to detail and the ability to maintain accuracy while performing repetitive, visually intensive work for extended periods.


• Strong spatial reasoning skills, including the ability to interpret 3D environments and understand object size, position, and orientation.


• Ability to learn and navigate complex, purpose-built software and become productive with keyboard shortcuts and other tooling features.


• Experience working in a fast-paced, scaled environment with defined productivity, quality, or accuracy targets.


• Experience with image annotation GenAI workflows.


• Reliable high-speed internet, a distraction-free workspace, and the ability to work on a company-provisioned machine within a controlled environment.

Nice to Haves

• Associate or bachelor's degree.


• Experience with image, video, LiDAR, or 3D annotation tools.


• Experience with subsurface utility engineering (SUE), construction surveying, surveying, GIS, or other work involving spatial interpretation of physical environments.


• Experience with AutoCAD or similar tools.


• Experience in construction, mining, agriculture, industrial operations, or heavy equipment environments.


• Familiarity with point cloud data, sensor fusion, or camera-LiDAR calibration.


• Experience working with autonomous vehicles, robotics, or machine perception datasets.

Why You'll Love Working Here

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At Appen , we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest-quality AI solutions for frontier models.

You'll work on complex challenges that shape the future of AI across industries and geographies, alongside talented people in a culture that values humility over ego. You'll have the flexibility to deliver in a way that works for you and your team, supported by tools, resources, and development opportunities to continue to build your capability over time.

About Appen

Appen has been a leader in AI training data for over 30 years. We specialise in human-generated data to train, fine-tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI-assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre-training, supervised fine-tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.

Is this Data Annotation Analyst role fully remote? Yes, the role is remote. However, you must work on a company-provisioned machine within a controlled environment, which requires a stable US-based home workspace with reliable high-speed internet. What types of data will I be annotating in this role? You'll annotate 2D and 3D objects across camera images, video sequences, and LiDAR point clouds, including vehicles, machinery, people, signage, and environmental terrain features. Is prior experience with LiDAR or 3D annotation required? No — LiDAR and 3D annotation experience is listed as a \"Nice to Have\", not a strict requirement. Strong spatial reasoning and attention to detail are the core must-haves. What is the salary for this position? No salary range is disclosed in the job posting. Candidates are encouraged to inquire about compensation details directly with Appen during the interview process. What background is ideal for this role beyond annotation experience? Appen specifically values experience in GIS, construction surveying, subsurface utility engineering, mining, agriculture, or autonomous vehicles — fields involving spatial interpretation of physical environments.

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