AI Engineer with less than a year in Machine Learning & Automation
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Result-oriented AI/ML Engineer with hands-on experience in machine learning, backend development, workflow automation, and intelligent application development. Skilled in Python, FastAPI, React, REST APIs, Generative AI, NLP, and automation workflows. Proven track record delivering measurable performance improvements in healthcare, education, and productivity systems.
Yenepoya Institute of Technology
B.E. · Artificial Intelligence & Machine Learning
August 1, 2022 – June 30, 2026
CoE-AI, NIT Calicut
AI Research Intern
February 1, 2026 – April 1, 2026
India
InternsForge
AI/ML Intern
August 1, 2025 – October 1, 2025
India
AI-Powered Virtual Nurse
January 1, 2025 – December 31, 2025
Built async FastAPI healthcare assistant supporting 150+ concurrent queries at <200ms latency with 94% satisfaction rate.
TalkEasy: AI Language Learning Platform
January 1, 2025 – December 31, 2025
Interactive platform with real-time pronunciation scoring for 500+ sessions; reduced transcription WER by 18%.
Lexy: AI Life Assistant (Google Gemini LLM)
January 1, 2025 – December 31, 2025
Autonomous FastAPI assistant orchestrating 12+ daily workflows with Human-in-the-Loop validation, saving 5+ hrs/week.
Runner-Up - ISTE Student Convention Hackathon
Unknown
January 1, 2025 – Present
Runner-Up - Agentic AI & Cloud Services Hackathon
Unknown
January 1, 2025 – Present
Python for Data Science & Machine Learning
IBM Cognitive Class
January 1, 2024 – Present
MongoDB Fundamentals
MongoDB Inc.
January 1, 2024 – Present
Git, Java & R Programming
IIT Bombay Spoken Tutorial Project / NPTEL
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's academic projects cover diverse applications of AI, including healthcare, language learning, and personal assistance, indicating a broad interest in applying AI solutions. Their internship experiences at CoE-AI, NIT Calicut, and InternsForge, along with hackathon participation, suggest an eagerness to learn and contribute. The target role of 'AI Engineer' aligns well with their educational background in AI & Machine Learning and their project/internship focus. The breadth of technical skills listed (Python, Java, JavaScript, SQL, various frameworks, AI/ML concepts, tools like Docker, Kubernetes, AWS, GCP) indicates adaptability and a willingness to explore different technologies, which is beneficial for cultural fit in a dynamic engineering environment. However, the candidate is still pursuing their bachelor's degree, which might impact immediate senior-level cultural fit expectations regarding extensive industry experience and mentorship capacity.
Soft Skills & Operational Fit
The candidate demonstrates a results-oriented approach, as highlighted by quantifiable achievements in projects and internships (e.g., 94% satisfaction rate, 18% WER reduction, 15% training efficiency increase). Their involvement in hackathons suggests a proactive and competitive attitude. The project descriptions indicate an ability to work on complex, multi-faceted problems, which aligns with the demands of an AI Engineer role. However, without specific psychometric or English test scores, a deeper assessment of stress handling, team collaboration, and communication clarity beyond written descriptions is not possible.