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Neura Robotics

Cognitive robots with perception, manipulation, collaboration

AI Data Annotation Specialist - Mensch

Data Management +1Confirmed live in the last 24 hours
Full-timeNo salary listedIn-person

About the Job

Requirements

  • A degree in computer science, data science, engineering, or a related field is required.
  • At least 4 years of experience in machine learning operations, artificial intelligence, or software engineering is required.
  • Practical experience with data annotation tools and labeling workflows, such as Encord, CVAT, Label Studio, or comparable platforms, is required.
  • Experience with subtask annotation, ontology or taxonomy design, and visual question answering-style labeling is required.
  • Familiarity with robotics dataset formats and multimodal data structuring, such as LeRobot, RLDS, or Open X-Embodiment, is required.
  • Experience writing annotation guidelines or taxonomies is required.
  • Familiarity with vision-language models and large language models for auto-labeling, such as open-vocabulary detectors or Gemini- and GPT-class models, is required.
  • Basic data engineering knowledge is required, including handling large-scale or streaming data and formats such as ROS Bags or MCAP, as well as S3-like object storage.
  • Experience building backend services and tooling, such as Node.js/TypeScript and REST APIs, to integrate annotation platforms into internal data infrastructure is required.

Responsibilities

  • Design, build, and maintain automated, semi-automated, and human-in-the-loop data annotation pipelines, focusing on subtask labeling for long-horizon robot demonstrations.
  • Develop annotation workflows for language-based robot learning and visual question answering datasets, including instruction generation, subtask decomposition, and grounding natural language in visual and action data.
  • Ingest multimodal data, including video, depth, proprioception, gripper states, and language instructions, and integrate it into structured annotation workflows.
  • Apply pre-labeling techniques with foundation models, such as vision-language models and large language models, to accelerate annotation and reduce manual effort.
  • Define and implement data quality checks for inter-annotator agreement, label consistency, coverage analysis, and annotation drift detection.
  • Advance data curation initiatives, including dataset balancing, deduplication, failure-case mining, task-diversity analysis, and targeted data collection to close capability gaps.
  • Identify and resolve data quality issues, labeling inconsistencies, distribution bias, and gaps in task or skill coverage.

Desired Qualifications

  • Experience with cloud platforms such as AWS, GCP, or Azure.
  • Direct experience with embodied AI or teleoperation data.

About the Company

Neura Robotics

Cognitive robots with perception, manipulation, collaboration

Neura Robotics builds cognitive robots for industrial and service settings, combining perception, manipulation, and human collaboration. It develops both the hardware and the software stack for Physical AI, creating robot platforms like MAiRA, MAV, LARA and MiPA along with training infrastructure. The system works by integrating sensing, decision-making, and manipulation capabilities on a hardware-software stack that can be deployed in large-scale production, with the company planning robots fleets and NEURA Gyms for ongoing training and improvement. What sets Neura Robotics apart is its end-to-end approach to Physical AI, including a focus on mass production, an established global deployment plan, and a broad ecosystem of strategic backers and partners that support scaling and international expansion. The goal is to enable worldwide deployment of its robot platforms and associated training infrastructure, turning physical AI into widely available industrial and service automation.

Company size
501-1,000
Company stage
Series C
Total funding
$1.7B
Headquarters
Metzingen, Germany
Founded
2019

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