4 дня назад
AI Data Annotation Specialist (AI)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Data Annotation Specialist (AI): Building scalable annotation workflows and structured training datasets for multimodal foundation models connecting perception, language, and robot action with an accent on human-in-the-loop labeling, VQA data, and robot demonstration subtasks. Focus on integrating video, depth, proprioception, gripper, and language data, applying foundation models for pre-labeling, and detecting quality issues, bias, and coverage gaps.
Location: On-site in Metzingen / Riederich, Germany
Company
AI department focused on building multimodal training datasets for embodied robotics and foundation models.
What you will do
- Design and maintain scalable automated, semi-automated, and human-in-the-loop annotation pipelines for long-horizon robot demonstrations.
- Develop workflows for language-grounded robot learning and Visual Question Answering datasets, including instruction generation, subtask decomposition, and language grounding.
- Ingest and structure multimodal robot data, including video, depth, proprioception, gripper states, and language instructions.
- Apply vision-language models and large language models for pre-labeling and annotation acceleration.
- Implement data quality checks covering inter-annotator agreement, label consistency, coverage, and annotation drift.
- Lead curation initiatives such as dataset balancing, deduplication, failure-case mining, task diversity analysis, and targeted data collection.
Requirements
- Degree in Computer Science, Data Science, Engineering, or a related field.
- 4+ years of experience in machine learning operations, AI, or software engineering.
- Hands-on experience with annotation tools and workflows such as Encord, CVAT, Label Studio, or comparable platforms.
- Experience with subtask annotation, ontology or taxonomy design, and VQA-style labeling.
- Familiarity with robotics dataset formats such as LeRobot, RLDS, or Open X-Embodiment.
- Comfort with large-scale or streaming data, ROS bags, MCAP, S3-style object storage, and backend tooling such as Node, TypeScript, and REST APIs.
Nice to have
- Experience with AWS, GCP, or Azure.
- Experience writing annotation guidelines and taxonomies.
- Familiarity with VLMs and LLMs for auto-labeling, including open-vocabulary detectors and Gemini or GPT-class models.
- Direct exposure to embodied AI or teleoperation data.
Culture & Benefits
- Full-time employment in the AI department.
- On-site collaboration in Metzingen / Riederich.
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