Senior Annotation and Data Pipeline Manager

Genesis AI
United States
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringSkills: ["Technical leadership","Hands-on execution","Ownership","Comfort with ambiguity","Quality-focused judgment"]

Own the data engine that turns raw robot demonstrations into clean, labeled, training-ready datasets. Build and scale the annotation operation with validation to ensure label quality, define datasets and ontology in partnership with the model team, and automate trajectory annotation using vision-language models. Run internal and vendor labeling, close the loop from model evaluation failures into targeted collection, and drive improvements using metrics like inter-annotator agreement and label error rate.

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FursaFursa
Genesis AI
Genesis AI
2 months ago

Senior Annotation and Data Pipeline Manager

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 20 hours agoStatus: Live

Job Summary

Own the data engine that turns raw robot demonstrations into clean, labeled, training-ready datasets. Build and scale the annotation operation with validation to ensure label quality, define datasets and ontology in partnership with the model team, and automate trajectory annotation using vision-language models. Run internal and vendor labeling, close the loop from model evaluation failures into targeted collection, and drive improvements using metrics like inter-annotator agreement and label error rate.
Location: United States
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Manager level

Key Responsibilities

  • •Run the data engine, owning the loop from raw trajectory/video to training-ready datasets with validation for clean, correctly labeled data.
  • •Own datasets and ontology by deciding what gets annotated and how, designing the ontology with the model team for training implications.
  • •Automate annotation using vision-language models for trajectory annotation, language grounding, and data synthesis while maintaining quality.
  • •Stand up and scale the annotation operation for internal and vendor labeling against a quality bar and delivery schedule.
  • •Close the loop by converting real-robot evaluation failures into targeted collection/annotation work and improving metrics such as inter-annotator agreement, label error rate, and throughput.

Key Requirements

  • •4+ years scaling data or ML pipelines, including time leading the work, taking raw robot or embodied data to training-ready at volume.
  • •Strong Python (Pandas, NumPy, PyTorch) and SQL, with ability to build automation that reduces pipeline effort.
  • •ML literacy, including training vs. test and precision/recall, to design an ontology that improves model learning.
  • •Hands-on technical leadership running labeling operations while staying a contributor.
  • •Comfort moving fast in a research-paced environment and bringing order to ambiguity.
Experience:RoboticsEmbodied AIFrontier AIMachine learningData pipelinesData labeling
Skills:Technical leadershipHands-on executionOwnershipComfort with ambiguityQuality-focused judgment
Tech Stack:PythonPandasNumPyPyTorchSQLVision-language models

Company Brief

Genesis AI
Genesis AI is a global physical AI research lab and full‑stack robotics company building a universal robotics foundation model and horizontal platform to enable general‑purpose robots and scale automation of physical labor.
Industry: AI & Machine Learning
Company Size: Small (11 to 50 employees)
Growth: Early Stage Startup
Funding: Seed
Headquarters: Paris, France
Founded: 2024
WebsiteLinkedIn