TRACTIAN
TRACTIAN is transforming the industrial world by empowering frontline maintenance workers to achieve more. We’ve fused cutting-edge hardware with innovative software into one powerful platform, disrupting legacy systems and delivering smarter, faster solutions for our clients.
End-to-End Ownership: Define program objectives, timelines, and deliverables for multiple data labeling projects simultaneously.
Workflow Design: Create scalable SOPs (Standard Operating Procedures) and guidelines. You will decide when to use a "Consensus" model (multiple labelers per item) versus a "Single-Pass" model based on cost/quality trade-offs.
Risk Mitigation: Proactively identify bottlenecks (e.g., ambiguity in guidelines, tool downtime) and implement "Risk Mitigation Strategies" before they impact model training schedules.
Crowd/Team Oversight: Recruit, train, and manage a distributed team of annotators. Monitor "Throughput" (items/hour) and "Efficiency" to ensure productivity targets are met.
Vendor Relations: Act as the primary interface for external data vendors. Negotiate timelines, track budget utilization, and hold vendors accountable to accuracy SLAs (e.g., 98% quality on Gold Sets).
Performance Coaching: Implement data-driven feedback loops. If an annotator's quality drops, you will analyze their errors and provide targeted retraining materials.
Gold Set Management: Maintain a "Gold Set" (master answer key) to blindly test annotators.
Metric Analysis: Track and report on key quality metrics: Inter-Annotator Agreement (IAA), Accuracy, and Precision/Recall of the human labels.
Root Cause Analysis: When model performance dips, you will investigate the training data to determine if the issue stems from "Labeler Bias," "Guideline Drift," or "Edge Case Ambiguity."
Platform Operations: Help set up the UI/UX and configurations for the internal platforms used for labeling and annotation.
Reporting: Generate weekly executive dashboards using Excel/Google Sheets (Pivot Tables, VLOOKUP) to visualize "Spend vs. Output" and "Quality Trends" for stakeholders.
Experience: 3+ years in Data Operations, Program Management, or QA for Machine Learning/AI.
Technical Literacy: Familiarity with the AI lifecycle (Training vs. Validation vs. Test sets).
Operational Rigor: Experience writing technical documentation/guidelines that leave no room for interpretation.
Data Skills: Advanced proficiency in Excel/Google Sheets. (SQL experience is a strong plus).
Tool Proficiency: Hands-on experience with annotation platforms (e.g., Labelbox, Scale AI, Appen Global, CVAT).
• Competitive salary and stock options
• 30 days of paid annual leave
• Education and courses stipend
• Earn a trip anywhere in the world every 4 years
• R$1.035/month for meals allowance
• Health plan with national coverage and without coparticipation
• Dental Insurance: we help you with dental treatment for a better quality of life.
• Gympass and Sports Incentive: R$300/mo extra if you practice activities
