Resume

Work Experience

Machine Learning Engineer, F-Secure, Bengaluru, Karnataka, Oct 2025 – Present

Spearheaded the development of a production scam detection platform processing high-volume message traffic with low end-to-end latency and reliable platform uptime.
Engineered a WhatsApp-based scam scanner using an agentic workflow with NLP, multimodal ML models, and backend security services, improving scam detection coverage.
Established a privacy-preserving ML preprocessing pipeline with mandatory PII detection and anonymization, enabling compliant training and inference while improving usable labeled data volume.

Software Engineer – AI/ML, Sony India Software Centre, Bengaluru, Karnataka, Aug 2024 – Oct 2025

Partitioned DeepSeek and Phi-3 models by splitting transformer layers across memory-constrained Raspberry Pi and Jetson Nano for real-time inference; preserved 100% accuracy without compromising architectural integrity.
Deployed an AI-based image failure detection on Jetson Orin NX to detect defocus, off-centre framing, and exposure issues; achieved 82% accuracy, cut drone reshoots by 40%, and was adopted by 3+ U.S. energy clients.

AI/ML Trainee, Sony Finishing School @ IITM Pravartak, Chennai, Tamil Nadu, Feb 2024 – Aug 2024

Led cross-functional development of a CNN-based murmur detection system using Mel-spectrograms from digital stethoscope data, achieving 86% accuracy in early identification of pathological heart sounds for remote diagnosis.
Built a quality-gating pipeline for scanned legal documents using Otsu’s thresholding and custom blur detection; flagged low-quality pages for enhancement, reducing OCR extraction errors by 20% across 15K legal documents.
Secured a full-time offer from Sony India post-program, as a top 1% candidate based on performance and interview.

Associate Software Engineer – I, HighRadius, Hyderabad, Telangana, Jul 2022 – May 2023

Developed a LightGBM-based payment date prediction model using customer behavioral trends and historical transactions; enabled proactive prioritization of delinquent accounts, improving overdue invoice recovery by 25%.
Engineered a CatBoost-based classification system to evaluate deduction validity across 600k+ financial transactions; isolated high-confidence invalid claims with 93% accuracy, eliminating 73% of manual follow-ups.

Product Intern – Data Science, HighRadius, Bhubaneswar, Odisha, Aug 2021 – Jun 2022

Eliminated SQL bottlenecks in a high-throughput, asynchronous Java REST API powering ML-based payment prediction pipelines; reduced latency by 40% using CompletableFuture, batched queries, and MySQL indexes.
Crafted a scalable feature engineering pipeline leveraging Python (Pandas) and SQL to efficiently extract, transform, and aggregate critical variables from large transactional data, boosting ML model accuracy by 8%.

Designed a hybrid retrieval and reranking pipeline over 568K reviews and 74K products, combining BM25, dense retrieval, and cross-encoder reranking to improve NDCG@10 by 17.7% over BM25 baselines.
Devised a citation-grounded RAG system, leveraging query reformulation and evidence-based generation to achieve 97.5% faithfulness with 100% citation precision, while reducing hallucinations by 80% versus a naive baseline.
Built a search platform indexing 568K documents with OpenSearch, FAISS, MLflow and FastAPI, enabling hybrid retrieval workflows under sub-80 ms p95 search latency with ~100 QPS throughput.

Implemented a production Hybrid Ensemble (LightGBM/CatBoost) achieving 96% precision and 70% automation, with an automated regression gate to protect logic across a 16k+ sample test set.
Integrated a calibration layer (Isotonic Regression) reducing ECE to <0.02; deployed Prometheus/Grafana observability for real-time monitoring of decision ratios and latency in critical risk-based pricing.

Machine Learning: Scikit-learn, PyTorch, TensorFlow, Experiment Tracking, Model Serving, Observability
Generative AI Systems: LLMs, AI Agents, LangChain, LangGraph, RAG, FAISS, MCP, Inference Optimization
Information Retrieval & Search: BM25, Hybrid Retrieval, Cross-Encoder Reranking, Lucene, Search Evaluation
Computer Vision: CNNs, Vision Transformers, Object Detection & Segmentation, Edge AI Deployment, TensorRT
Engineering & Cloud: Python, Git, Docker, Linux, CI/CD, AWS (SageMaker, Bedrock, Lambda), ONNX, FastAPI

B.Tech in Electronics and Communications Engineering (Hons.), Lovely Professional University, Punjab, India
Graduation: June 2022

CGPA: 8.44
Relevant Coursework: Introduction to Artificial Intelligence, Digital Signal Processing, Database Management System, Workshop on Image Processing, Computer Programming, Data Structures and Algorithms