Jasveer Singh
Open to work1 years experienceAI/ML Engineer
AI/ML Research Intern at C-DAC | GenAI & Agentic Systems Developer
Standing Rank
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Skills & Technologies
30 skillsWork Experience
AI/ML Research Intern
Centre for Development of Advanced Computing (C-DAC)
- Built and deployed ML, DL, and LLM-powered pipelines for malware analysis and threat detection, applying GenAI workflows to real-world security datasets.
- Optimized model and feature engineering strategies across detection pipelines, achieving an 8% improvement in malware detection performance while iterating on prompt design and pipeline architecture.
- Translated applied AI/ML and GenAI research into working prototypes, documenting technical findings and benchmark results for publication-oriented projects.
Projects
ThreatForge: Multi-Agent AI Cyber Threat Intelligence Platform Architecture
- Architected a 6-agent LangGraph pipeline with a self-validating detection loop, orchestrating threat intelligence ingestion, IOC extraction, MITRE ATT&CK mapping, and autonomous security report generation.
- Engineered an AI-native intelligence pipeline integrating a Neo4j Knowledge Graph, semantic retrieval, and LLM reasoning to correlate threat entities and produce STIX 2.1 / TAXII 2.1 -compliant, analyst-ready threat intelligence.
- Decoupled inter-agent communication via Redis Streams with LiteLLM routing and Ollama/Groq fallback.
LMDA: Multi-Agent AI Honeypot and Threat Analysis Framework Architecture
- Architected a LangGraph-powered multi-agent honeypot framework orchestrating autonomous AI agents for real-time attacker interaction, session-based threat monitoring, and behavioral profiling of intrusion attempts.
- Engineered collaborative LLM agents for attack interpretation, anomaly detection, and automated incident reporting.
- Integrated LLM inference pipelines, memory-aware session state, and modular inter-agent communication.
MAL3S: Multi-Feature Malware Detection using CNN and Spatial Pyramid Pooling Networks
- Built a CNN + Spatial Pyramid Pooling Network malware classifier using multi-modal static feature representations.
- Improved detection performance by ~10% through targeted preprocessing, feature engineering, and model optimization techniques.
- Evaluated model robustness and interpretability using FGSM, PGD, and DeepFool adversarial attacks alongside Grad-CAM and SHAP explainability analysis.
Leaderboard Standings
Leaderboard Position Pending
Global test scores, peer standing percentiles, and algorithm leaderboard ranks are updated dynamically.
Assessment Highlights
Assessments Not Completed
Coding evaluations, system assessment results, and conceptual score badges will appear here after taking a test.
AI Collaboration Score
AI Collaboration Score Pending
Developer coding behavior, assistant cooperation, and AI pair-programming indicators are evaluated during live coding sessions.
Role Compatibility Profile
Role Compatibility Analysis Pending
Custom matching reports, candidate role compatibility percentiles, and core engineer strength profiles are processed once conceptual code screenings are complete.
Achievements
Smart India Hackathon (SIH) 2023 Finalist
Finalist in Smart India Hackathon (SIH) 2023 for developing an Intelligent Ladle Tracking System.
C-DAC BOSS Linux Bug Bounty Hackathon
Identified 3 critical vulnerabilities in BOSS OS during a 36-hour security research event.
Competitive Programming Achievements
Max rating 1533 (3★) on CodeChef; 184+ problems solved on Codeforces; 40+ problems solved on LeetCode.
About Details
Professional Bio
AI/ML developer specializing in GenAI, agentic systems, and cybersecurity. Experienced in building LLM-powered pipelines, multi-agent architectures, and malware detection models. Passionate about applied AI research and competitive programming.
Bachelor of Technology in Computer Science and Engineering
Sardar Beant Singh State University (2022 - 2026)
Class XII
Govt. Senior Secondary School, Hajipur ( - Present)