Join Skild AI as a Senior Master Annotator to define and improve annotation standards for robotic datasets.
Posted by employer 6 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Requirements
- Experience
- 4–7 years
Not disclosed in this posting: compensation, work arrangement, visa sponsorship.
Joblaze summary
In the role of Senior Master Annotator at Skild AI, the individual will focus on defining and enhancing annotation standards for diverse robotic datasets, ensuring high-quality labeling essential for model training. Key skills include expertise in various annotation types, particularly in video and 3D data, along with a strong grasp of quality metrics and Inter-Annotator Agreement methodologies. This position is ideal for candidates with 4-7 years of relevant experience who possess a detail-oriented mindset and a passion for mentoring others. The team values innovative thinking and a collaborative approach to tackling complex challenges in robotic intelligence.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Skild AI's career page.
- Skild AI has 63 other open roles including Manufacturing Engineering Manager, Senior Electrical Engineer , Operations Program Manager – Data Infrastructure - India.
- 247 active Robotics roles on Joblaze right now.
- 133 active Computer Vision roles on Joblaze right now.
- 53 active autonomous systems roles on Joblaze right now.
- Typical Robotics salary we track runs $100,000–$177,000 (median $142,500, across 84 roles).
Quick facts
- How much experience is required?
- 4–7 years of relevant experience for this Senior Master Annotator role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: Computer Vision, Quality Control, Robotics, autonomous systems, data annotation, video labeling.
- What seniority level is this role?
- Skild AI targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Senior Master Annotator role at Skild AI.
From the original posting
Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
Position Overview
We are looking for a highly detail-oriented and technically strong Senior Master Annotator to define, maintain, and continuously improve annotation standards for robotic datasets. Various type of data sets can be generated which needs to be annotated and quality checked before they are put in production
This role will act as the gold standard authority for labeling tasks, own Inter-Annotator Agreement (IAA) measurement, train and calibrate annotators, and ensure that annotation quality meets the high standards required for robotics model training.
The ideal candidate understands image, video, 3D and audio annotation, quality metrics, and how annotation accuracy impacts model performance.
Responsibilities
- Define and maintain gold-standard annotations and benchmark (“gold set”) datasets for new and existing tasks
- Establish clear acceptance criteria, tolerance thresholds, and task-specific quality standards (e.g., frame-level tolerances)
- Develop, document, version-control, and continuously refine annotation guidelines and SOPs based on disagreement patterns and quality findings
- Design and implement Inter-Annotator Agreement (IAA) frameworks (e.g., Cohen’s/Fleiss’ kappa, tolerance-based agreement models) and produce regular quality reports
- Analyze disagreement trends, identify root causes, and recommend data-driven process improvements
- Lead onboarding and ongoing training for annotators, including structured calibration sessions
- Build and maintain edge-case libraries and example banks to improve annotation consistency
- Provide targeted feedback and retraining to improve annotator performance and alignment with gold standards
- Conduct precision-based QC audits according to task requirements and validate pilot batches prior to production scaling
- Review escalated edge cases and partner with QA and Operations teams to optimize sampling strategies and quality processes
Preferred Qualifications
- 4–7+ years of experience in data annotation, quality control, or video labeling environments
- Strong expertise in temporal video annotation; experience with robotics, computer vision, or autonomous systems datasets preferred
- Deep understanding of Inter-Annotator Agreement methodologies (e.g., Cohen’s/Fleiss’ kappa), quality metrics, sampling strategies, and gold set creation
- Experience mentoring, training, or guiding annotators to improve accuracy and consistency
- Strong analytical skills with proficiency in Excel or Google Sheets (Python preferred but not required)
- Ability to translate ambiguous SOPs into precise, actionable annotation guidelines
- Exceptional attention to detail and sound judgment in ambiguous visual tasks
- Data-driven, process-oriented mindset with strong ownership and accountability
- Excellent written and verbal communication skills