Tesla Hiring Data Labeler 2024 | Apply Now

Role: Data Labeler Location: Draper, Utah
Job Type: Full-time Company: Tesla Salary: Not Disclosed Shift: 9:00 AM – 5:30 PM
Table of Contents Toggle Data Labeler Job Description Data Labeler Roles Data Labeler Responsibilities Data Labeler Skills Data Labeler Education and Qualifications Data Labeler Conclusion Data Labeler Job Description
Data Labelers annotate datasets with precision, ensuring accuracy and compliance with hints. Responsibilities consist of satisfactory manipulation, documentation, and collaborating with groups to optimize workflows. Essential capabilities encompass attention to detail, hassle-fixing, and flexibility. Candidates usually have a high college diploma or equivalent, with experience in data annotation or associated fields preferred. Data Labeler Roles Data Annotation: Accurately labeling facts in line with distinctive hints. Quality Control: Ensuring extraordinary annotations through meticulous evaluation. Workflow Management: Organizing and prioritizing obligations to fulfill deadlines. Communication: Collaborating with group members to solve labeling-demanding situations. Adaptability: Adjusting to evolving labeling requirements and gear. Data Labeler Responsibilities Labeling numerous datasets with precision and consistency. Performing first-class assessments to keep statistics integrity. Documenting labeling choices and comments for development. Following guidelines to ensure compliance and accuracy. Reporting troubles and suggesting improvements in labeling methods. Prioritizing tasks primarily based on assignment timelines and necessities. Collaborating with records scientists and engineers to optimize labeling workflows. Adapting to new gear and strategies for data annotation. Participating in schooling sessions for brand-spanking new labeling responsibilities. Maintaining confidentiality and protection of classified data. Data Labeler Skills Attention to detail and accuracy. Critical questioning and hassle-fixing capabilities. Ability to work independently and in a team. Time control and organizational abilties. Effective communique (written and verbal). Adaptability to changing mission necessities. Familiarity with facts annotation tools (e.g., Labelbox, Scale AI). Basic know-how of machine mastering ideas. Knowledge of statistics privacy policies (e.g., GDPR, HIPAA). Basic talent in spreadsheet and records management software. Data Labeler Education and Qualifications High college degree or equivalent; bachelor’s degree preferred. Previous revel in statistics access, annotation, or comparable roles. Certification in data annotation equipment or related fields (preferred). Familiarity with precise enterprise domain names (e.g., healthcare, automotive). Proficiency in applicable languages or software program gear (Python, SQL, and so on.). Understanding of statistical evaluation and facts interpretation. Ability to handle massive datasets and complicated labeling tasks. Strong analytical and hassle-fixing talents. Training in nice warranty or process development. Excellent documentation and file-retaining competencies. Data Labeler Conclusion Data labelers play a critical role in making ready datasets for devices gaining knowledge of AI programs by ensuring accurate and reliable annotations. This function requires a blend of technical competencies, attention to element, and powerful communique, making it essential in the improvement of superior technologies across numerous industries.