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ML Engineer with less than a year in GenAI & Production Systems
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ML Engineer with production experience building content safety pipelines, LLM-powered classification systems, and high-throughput distributed backends. Shipped scalable GenAI systems with FAISS vector search, RAG pipelines, and multimodal inference deployed on Azure, serving 50+ concurrent users with measurable gains in accuracy, latency, and reliability.
The Northcap University
Bachelor of Technology · Computer Science and Engineering, Specialization in AI&ML
August 1, 2022 – June 30, 2026
Fourth Square
Computer Analyst Intern
June 1, 2025 – August 1, 2025
India
Alstonia Consulting LLP.
OracleDB Manager Intern
June 1, 2024 – July 1, 2024
New Delhi, Delhi, India
Image Anomaly Detection
May 1, 2026 – June 1, 2026
Engineered an MVTec AD → YOLO pipeline via OpenCV, extracting bounding boxes from segmentation masks to train on anomaly data (analogous to noisy abuse-signal classification). Trained YOLOv8s on 26 defect classes; designed custom per-class augmentations (mosaic, mixup) to resolve severe imbalances, mirroring UGC abuse data dynamics. Deployed a production-ready FastAPI endpoint via Docker and shipped a Gradio web UI for real-time bounding box visualization and JSON analytics.
View ProjectFarmEZ
October 1, 2025 – June 1, 2026
Architected an agentic agriculture assistant via LangChain tool-calling and Ollama LLM inference, engineering FastAPI REST endpoints for async sensor CSV ingestion. Designed a 100% on-device inference stack with Whisper STT/TTS for multilingual voice interaction, achieving ¡3s latency and 2-3 tok/s throughput via an async non-blocking architecture.
View ProjectResume ATS Tracker
August 1, 2025 – February 1, 2026
Scaled pipeline to handle 150 req/min across 50+ concurrent users; integrated Redis caching (~90% hit rate) to slash AI latency from 20s → ¡500ms and meet throughput SLOs. Engineered a RAG pipeline (LangChain, Gemini 2.5) with FAISS IVF indexing for k-NN search, accelerating semantic retrieval 10x vs. brute-force (O(logn) at 10K vectors). Deployed to Azure serverless via multi-stage Docker & GitHub Actions CI/CD, implementing stateless horizontal scaling, Redis rate-limiting, and agentic workflows.
View ProjectPython for Everybody
University of Michigan - Coursera
June 1, 2026 – Present
Machine Learning Specialization (Supervised ML, Advanced Algorithms, Unsupervised Learning & RL)
Stanford University & Deeplearning.AI - Coursera
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects (Image Anomaly Detection, Resume ATS Tracker, FarmEZ) showcase initiative, a broad interest in AI/ML applications, and a drive to build end-to-end solutions. The internship experience at Fourth Square, involving work across USA/India time zones, indicates adaptability and a collaborative mindset. The specialization in AI&ML and relevant certifications further demonstrate a strong commitment to the field, aligning well with a culture that values continuous learning and innovation.
Soft Skills & Operational Fit
The candidate's project descriptions and internship experience demonstrate a proactive approach to problem-solving, a focus on performance optimization, and an understanding of production deployment challenges. The ability to manage technical debt and work in agile sprints suggests good operational fit. The detailed descriptions imply strong communication skills in a technical context.