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Appen is seeking a Data Annotation Analyst to label 2D and 3D data across images, videos, and LiDAR. You will create precise segmentation, tracking, pose, and keypoint annotations following strict guidelines while maintaining high quality and production throughput.
You will review work, address QA feedback, and escalate ambiguous scenes. This role supports calibration sessions and contributes to edge-case documentation in a fast-paced environment.
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.
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.
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.