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AI Engineer with less than a year in Machine Learning & Data-driven Applications
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Computer Science graduate with a strong foundation in AI, machine learning, and backend development. Experienced in building data-driven applications, and intelligent automation systems. Passionate about applying AI to real-world problems and continuously expanding technical expertise through hands-on learning and collaboration.
NED university of engineering & technology
bachelor of science · computer science
August 1, 2022 – June 30, 2026
BENCHMATRIX
AI ENGINEER
January 1, 2026 – Present
India
FOLIO3
ARTIFICIAL INTELLIGENCE INTERN
October 1, 2025 – November 1, 2025
India
NEUROCOMPUTATION LAB - NCAI
MACHINE LEARNING INTERN
August 1, 2024 – October 1, 2024
India
TISAR - THREAT INTELLIGENCE SCORING AND ANALYSIS
June 24, 2026 – Present
Built a FastAPI + LangGraph multi-agent CTI pipeline (attribution, TTP mapping, citation validation agents) enriching IoCs across 4 threat intel APIs to automate threat intelligence inference. Engineered a two-gate false positive detection system with deterministic scoring to deliver high-confidence verdicts while cutting redundant API calls. Implemented automated threat report generation with TLP classification and confidence tiering to produce analyst-ready outputs at scale.
Research Assistant Agent
June 24, 2026 – Present
Built a Streamlit interface integrated with Google Gemini for real-time, customizable paper searches. Developed a custom scoring system to rank papers based on relevance, author influence, citations, and publication age. Streamlined the solution using LangChain Core, improving maintenance and speeding up feature development.
INTROVERT-EXTROVERT PREDICTION
June 24, 2026 – Present
Identified missing-data patterns using synthetic missingness and linear regression to select the optimal imputation strategy. Implemented and evaluated multiple imputation methods to improve dataset completeness and model reliability. Trained and compared several ML models to ensure strong generalization on unseen data.
Cultural Fit Analysis
The candidate's diverse project portfolio, ranging from threat intelligence to research assistants and predictive modeling, indicates a broad interest in applying AI across various domains. Their involvement in a cross-university team and internships suggests an ability to collaborate and adapt to different work environments. The continuous learning mentioned in the profile aligns with a growth-oriented culture. The target role of 'AI Engineer' aligns well with their demonstrated skills and project focus.
Soft Skills & Operational Fit
The candidate demonstrates a proactive approach to learning and applying AI concepts to real-world problems. Their project descriptions highlight collaboration and a results-oriented mindset. The experience in automating tasks suggests an operational fit for roles requiring efficiency and system integration. However, without specific psychometric test results, a deeper assessment of stress handling, logical reasoning, and team collaboration is not possible.