AI Engineer with less than a year in data annotation & quality assurance.
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Assessing your cultural and operational fit
Detail-oriented Artificial Intelligence & Machine Learning undergraduate with experience in data annotation, quality auditing, data validation, and operational support. Skilled at reviewing large volumes of data, identifying inconsistencies, and maintaining high accuracy standards under productivity targets. Experienced in following standard operating procedures (SOPs), performing quality checks, and documenting results. Strong focus, analytical thinking, and communication skills with the ability to work effectively in fast-paced, rotational-shift environments.
Shadan College of Engineering & Technology (JNTUH)
Bachelor of Technology (B. Tech) · Artificial Intelligence & Machine Learning (AI&ML)
November 1, 2022 – April 1, 2026
Sultan-u-Uloom Junior College
12th Class · Mathematics, Physics and Chemistry (MPC)
June 1, 2020 – May 31, 2022
Transaction Data Classification System
June 22, 2026 – Present
Reviewed and classified 5,000+ transaction records while maintaining high accuracy standards. Performed detailed audits to identify and resolve inconsistencies in data. Conducted validation checks and maintained operational tracking using Microsoft Excel. Followed structured review processes to ensure data quality and reliability. Achieved 95%+ accuracy while meeting project deadlines.
Product Catalog Data Annotation Project
June 22, 2026 – Present
Audited and annotated large datasets following predefined quality guidelines. Identified and corrected data errors through systematic validation processes. Maintained consistency and accuracy across high-volume annotation tasks. Documented findings and ensured compliance with project standards. Contributed to improving dataset quality through continuous review and verification.
Cultural Fit Analysis
The candidate's academic projects indicate a focus on data quality and annotation, which aligns with entry-level AI/ML data preparation roles. Their stated work style emphasizes collaboration and adaptability, suggesting a positive cultural fit for team-oriented environments. However, the breadth of technical skills is limited to data annotation and basic tools, which might require significant upskilling for a senior AI Engineer role.
Soft Skills & Operational Fit
The candidate demonstrates strong attention to detail, focus, and accuracy in repetitive tasks. They are comfortable with rotational shifts and possess good communication skills, which are beneficial for collaborative environments. Their ability to adapt to new tools and processes suggests a good operational fit for roles requiring continuous learning and process adherence.