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Nyxel User

@nyxeluser

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AI automation and machine learning intern building production-ready LLM pipelines and predictive systems.

India

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What I'm looking for

I’m looking for an AI/ML opportunity where I can build reliable LLM automations, ship production-ready systems quickly, and grow by working with a team that values both experimentation and deployment quality.

I’m a machine learning and AI automation intern who focuses on turning models into production workflows. At Fortiv Solutions, I spearheaded AI automation serving 5+ enterprise clients and cut manual processing time by 70% by integrating CRM systems (HubSpot, Pipedrive), LLM APIs (OpenAI GPT-4, Claude, Gemini), and databases.

I also build high-performing ML/DL systems end-to-end: from training (Random Forest, XGBoost, SVM; TensorFlow 2.x/Keras CNNs) to deployment with tools like Streamlit. My projects include an ML-based crop yield predictor (87% prediction accuracy, R² = 0.85) and a real-time wildfire detection system (92% accuracy, 88% F1-score) with optimized inference under 100ms.

Experience

Work history, roles, and key accomplishments

AI Automation Intern

Fortiv Solutions

Jan 2026 - Mar 2026 (2 months)

Spearheaded production-scale AI automation serving 5+ enterprise clients, reducing manual processing time by 70%. Built 15+ n8n workflow automations integrating HubSpot/Pipedrive with GPT-4/Claude/Gemini, processing 1K+ documents monthly with an 85% automation success rate, and reduced contract review time from 4 hours to 15 minutes per case.

AI Automation GPT 4 Anthropic: Claude Document Processing Contract Analytics

Machine Learning Intern

Edunet Foundation

Jun 2025 - Jul 2025 (1 month)

Developed supervised learning models (Random Forest, XGBoost, SVM) achieving 89% classification accuracy for sustainability impact prediction. Built CNN pipelines with TensorFlow 2.x/Keras (ResNet, EfficientNet) for satellite imagery analysis reaching 91% validation accuracy, and improved automated ML workflows to reduce model iteration time by 60%.

Machine Learning Random Forest XGBoost SVM TensorFlow Keras CNNs (ResNet EfficientNet)Satellite Imagery Analysis Hyperparameter Tuning

Education

Degrees, certifications, and relevant coursework

Ahmedabad Institute of Technology

Bachelor of Technology (B.Tech), Computer Engineering

Grade: GPA: 8.75/10.0

Activities and societies: Relevant coursework: Machine Learning, Deep Learning, Natural Language Processing, System Design, Computer Networks, Data Structures & Algorithms.

Pursuing a B.Tech in Computer Engineering at Ahmedabad Institute of Technology, with an expected graduation of May 2026. Coursework includes machine learning, deep learning, natural language processing, system design, computer networks, and data structures & algorithms.