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AI Engineer with 1+ years in Data Analytics and AI/LLM workflows.
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Assessing your cultural and operational fit
Highly motivated junior AI Engineer with 1.1 years of experience across AI training, data analytics, and machine learning projects. Skilled in reviewing AI-generated content for correctness, analyzing operational datasets to identify trends, and automating reports. Proficient in SQL, Python, Power BI, and foundational cloud technologies, with a strong background in developing AI/ML-assisted solutions for data query and performance tracking.
Netaji Subhas University of Technology (NSUT), Delhi
Bachelor of Technology · Information Technology
August 1, 2022 – June 30, 2026
Invisible Technologies
AI Trainer Specialist
September 1, 2025 – Present
India
Idyll AI
Analyst Intern
October 1, 2024 – January 1, 2025
India
Auto-SQL: Analytics Query Assistant
December 1, 2025 – Present
• Designed a prototype workflow to convert natural-language business questions into SQL queries. • Used rule-based logic with ML-assisted suggestions to reduce incorrect outputs. • Applied the tool for faster exploratory analysis during coursework.
Vendor Performance Dashboard
August 1, 2024 – Present
• Built Power BI dashboards to track vendor delivery timelines and issue frequency. • Enabled centralized reporting to replace manual tracking.
Cultural Fit Analysis
The candidate's academic projects and internships show a proactive approach to learning and applying technical skills. Their involvement in academic initiatives and leadership roles (Head of Council, Trip Manager) suggests a collaborative mindset and ability to take initiative. The diverse exposure to data analysis, AI training, and basic ML workflows indicates adaptability and a willingness to explore different technical areas, which aligns well with dynamic AI roles.
Soft Skills & Operational Fit
The candidate demonstrates problem-solving skills through project work and an ability to contribute to operational improvements (e.g., automating reports). Their current role as an AI Trainer Specialist suggests attention to detail and a focus on improving system reliability. The academic projects indicate an ability to apply learned concepts to practical scenarios.