Headline

AI/ML Engineer | GenAI · RAG · Agentic AI | FastAPI · LangChain · AWS | Ex-DRDO AI/ML Intern | IEEE Published

About

AI Engineer with hands-on experience building production-grade AI systems at DRDO (Ministry of Defence, Govt. of India) and an IEEE-published researcher in 3D object detection. I build things that ship — RAG pipelines, LLM-powered applications, computer vision models, and full-stack AI products — using FastAPI, LangChain, PyTorch, AWS, and Docker. Currently pursuing B.E. in Artificial Intelligence & Machine Learning at ATME College of Engineering, Mysuru (CGPA: 9.71) | Available from mid-2026 | Open to relocation. What I build: 🤖 GenAI & Agentic AI — RAG pipelines, LLM-powered workflows, AI agents using LangChain & Claude API ⚙️ Full-Stack Applications — FastAPI + React backends, REST APIs, AWS-based cloud deployments with Docker 📊 ML Solutions — malware detection systems, computer vision (EfficientNet, Grad-CAM), predictive models 🔁 MLOps & Automation — model lifecycle management, workflow automation, voice-driven AI interfaces Tech Stack: Python · FastAPI · React · LangChain · PyTorch · AWS · Docker · PostgreSQL · Git · HuggingFace At Cognifyz Technologies, I worked end-to-end on ML projects — from raw data preprocessing and feature engineering to model deployment — building the engineering discipline that separates ML practitioners from ML engineers. Beyond internships, I've independently built AI-powered SaaS products (ClientProof AI, DevLaunch AI) from zero to MVP, using Next.js, Supabase, Stripe, and Claude API — validating ideas with real users before scaling. I care about clean architecture, measurable impact, and systems that work outside the lab. 📍 Mysore, India | Open to relocation | Available from mid-2026 📬 farhaansyed34@gmail.com | github.com/syedfarhaan-dev

Location

Mysore

Work experience

AIML Engineer at DRDO, Ministry of Defence, Govt. of India, Dec 2025 - May 2026 · 6 mos, Bengaluru, Karnataka, India, AI & Machine Learning Engineer Intern • Developed and optimized machine learning and deep learning solutions for mission-critical defence applications, working under stringent reliability, security, and performance constraints • Built end-to-end ML pipelines involving data acquisition, preprocessing, feature engineering, model training, evaluation, and validation on sensitive, non-public datasets •Applied computer vision and deep learning techniques to real-world classification and detection challenges, balancing robustness, inference efficiency, and predictive performance. • Collaborated with DRDO scientists and research teams to translate complex problem statements into deployable AI solutions aligned with operational requirements • Contributed to AI research workflows, model experimentation, performance benchmarking, and technical documentation within a high-security R&D environment • Operated within production-oriented AI infrastructure and secure research environments, contributing deployable solutions under the same reliability standards applied to defence-grade systems Skills: Python • PyTorch • Machine Learning • Deep Learning • Computer Vision • Data Engineering • Research • Model Evaluation • Secure AI Systems

Head of Creative committee in IET at IET ATMECE STUDENT CHAPTER, Jan 2025 - Mar 2025 · 3 mos, Karnataka, India, Led the Creative Committee of the IET (Institution of Engineering and Technology) Student Chapter at ATME College of Engineering, managing content strategy and visual communication for technical events. • Directed design and branding for chapter events, workshops, and outreach campaigns, increasing engagement among 300+ student members. • Coordinated cross-functional teams of 8+ student volunteers, managing timelines, deliverables, and creative direction simultaneously. • Produced event collateral, social media content, and promotional material that elevated chapter visibility within the college and region Skills: Leadership · Team Management · Event Planning · Creative Direction · Communication

Machine Learning Intern at Cognifyz technology, Oct 2024 - Mar 2025 · 6 mos, Maharashtra, India, Machine Learning Intern • Delivered end-to-end machine learning solutions across multiple project domains, covering data acquisition, preprocessing, feature engineering, model development, evaluation, and deployment preparation • Engineered feature extraction and transformation pipelines for structured datasets, improving model performance through domain-driven feature selection and optimization • Implemented and benchmarked machine learning algorithms including Random Forest, XGBoost, and Neural Networks, selecting optimal models based on accuracy, interpretability, and business requirements • Built robust data preprocessing workflows involving missing value treatment, outlier analysis, normalization, and data quality validation to improve downstream model reliability • Performed exploratory data analysis (EDA), model validation, hyperparameter tuning, and performance evaluation to generate actionable insights from complex datasets • Produced technical reports, model documentation, and reproducible workflows aligned with industry best practices for machine learning development Skills: Python • Scikit-learn • XGBoost • Pandas • NumPy • Feature Engineering • Machine Learning • Model Evaluation • EDA • Data Preprocessing

Education

Bachelor of Engineering (Artificial Intelligence & Machine Learning), AIML, ATME College of Engineering, Mysuru