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AI Engineer with less than a year in NLP, Machine Learning, and Cloud platforms (Azure & AWS)
Ladi Santosh is an aspiring Azure Cloud Engineer and Generative AI Developer, currently pursuing a B.Tech in Computer Science & Engineering. With practical experience as a Research Intern at CloudThat Technologies and a Full Stack Developer Intern at IBM Solutions, Ladi has honed skills in PyTorch, TensorFlow, NLP, LLM, and cloud infrastructure. Key achievements include fine-tuning sentiment models, engineering ML pipelines, and deploying scalable cloud solutions, demonstrating a strong foundation in AI development and cloud engineering.
Lovely Professional University
B.Tech · Computer Science & Engineering
N/A – June 30, 2026
CloudThat Technologies
Research Intern – Multi-Cloud (Azure & AWS)
January 1, 2026 – Present
Bengaluru, Karnataka, India
IBM Solutions
Full Stack Developer Intern
May 1, 2024 – July 1, 2024
India
IntelliDoc
June 24, 2026 – Present
RAG chatbot with NLP preprocessing and embedding fine-tuning (92%+ accuracy)
Azure Cloud App
June 24, 2026 – Present
Auto-scaling deployment with 99.9% uptime
Microsoft Azure Fundamentals AZ-900
Microsoft
June 1, 2026 – Present
AWS Certified Cloud Practitioner
AWS
January 1, 2025 – Present
MySQL Certification
HackerRank
January 1, 2024 – Present
Cultural Fit Analysis
The candidate shows a strong interest in AI/ML and cloud technologies, aligning well with an AI Engineer role. Their involvement in both research and full-stack development internships, along with personal projects, demonstrates versatility and a willingness to explore different areas. However, the candidate is still pursuing their bachelor's degree, which might indicate a need for mentorship and structured guidance in a professional setting. The breadth of skills and certifications suggests a continuous learning mindset.
Soft Skills & Operational Fit
The candidate's resume indicates a proactive approach to learning and applying new technologies, as evidenced by their diverse project work and certifications. Their experience in optimizing models and deploying scalable solutions suggests a results-oriented mindset. The descriptions of their internship roles highlight collaboration and problem-solving skills, which are crucial for operational fit.