Antonio S.
AI and Data Science , Information Technology , Operations
(214) GO-RELAY / (214) 467-3529
Careers@RelayHumanCloud.com
Ahmedabad, India
SKILLS
- Python
- SQL
- Advanced Excel
- Github
- Agentic AI
- AWS
- Oracle
- C/C++
- TensorFlow
- Pytorch
- Scikit-learn
- Pandas
- Numpy
- Gemini API
- FastAPI
- OpenAI
- DeepLearning
- Docker
- Deepgram
- Twilio
- Linux
- Streamlit
- Management
- Communication
EDUCATION
Bachelor of Technology (Computer science and Engineering)
Heritage Institute of Technology (2025)
LICENSES & CERTIFICATIONS
- OCI Data Science Professional | Oracle
- OCI Generative AI Professional | Oracle
- Machine Learning Specialization | Coursera
- CyberSecurity Professional Certificate | Google
- Introduction to Generative AI | Google
PROFESSIONAL SUMMARY
Results-driven Junior Software Developer with hands-on experience in AI/ML development, including deep learning and real-time AI integration. Skilled in Python, SQL, and frameworks such as TensorFlow and Pytorch. Expertise in building scalable AI models, improving system latency, and automating processes. Proven ability to design efficient data pipelines and deploy machine learning models for high-impact business solutions. Adept at optimizing LLM performance and system throughput to enhance response time and platform stability. Strong background in developing end-to-end AI workflows, including data preprocessing, model deployment, and automation for real-time applications.
PROFESSIONAL EXPERIENCE
AI Developer Intern
YourAllyStack | India | Sept 2025 - Jan 2026
- Developed an AI-driven interview question generation engine, integrating RESTful APIs with Google Gemini and OpenAI models, automating domain-specific question setups and reducing manual interview setup by 90%.
- Enhanced system performance by optimizing LLM latency and throughput through prompt compression, token usage tracking, and model routing, reducing response time by 70-80% and improving platform stability.
DeepLearning Research Intern
Institute of Infrastructure Research and Management | India | June 2024 - July 2024
- Researched ML/DL-based sleep stage classification, achieving 86% accuracy using non-invasive PPG signals.
- Developed and implemented ML models with residual convolutional blocks and temporal convolutional networks, improving predictive accuracy by 10-15% compared to traditional methods.
- Orchestrated data cleaning and preprocessing workflows using Pandas and Scikit-learn, resulting in a 15% reduction in model error rates by eliminating noise in sleep stage classification datasets.
