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AI Engineer with 1+ years in Machine Learning, Fullstack Development & Cloud
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Highly motivated Computer Science student with 1.5 years of experience as a Software Engineer Intern and Research Assistant, specializing in AI, Machine Learning, and Fullstack Development. Proven ability to build and optimize AI-powered tools, architect scalable cloud-native applications, and develop robust backend systems. Experienced in various technologies including Python, Node.js, React, PostgreSQL, AWS, and LLM frameworks, with a strong focus on delivering impactful technical solutions and improving system performance.
University of California, Santa Cruz (UCSC)
Bachelor of Science · Computer Science
N/A – June 1, 2026
Dream Enrichment
Software Engineer Intern
April 1, 2026 – Present
India
BestPeers - Softverse Systems
Software Engineer Intern
June 1, 2025 – September 1, 2025
India
Wildcard AI - YC W25
Software Engineer Intern
March 1, 2025 – June 1, 2025
India
AIEA Lab
Research Assistant
December 1, 2024 – June 1, 2025
India
UCSC Rideshare
February 1, 2026 – February 1, 2026
Cross-platform React Native app connecting UCSC students for ride coordination, leading a 5-person team. Go backend using Echo framework handles JWT auth and 15+ RESTful endpoints for user and ride management. Google Maps integration with Places API and Routes API for route visualization and location services. Ride request system tracks status changes and automates driver-passenger matching workflow.
Wiki Information Retrieval System
January 1, 2025 – January 1, 2025
RAG LLM system integrates FAISS vector search with Transformers for document retrieval and answer generation. Vector database search handles concurrent queries, achieving sub-200ms response times. BeautifulSoup scraping extracts structured data from complex Wiki layouts with 93% accuracy. Llama 3 model synthesizes multiple retrieved document chunks into comprehensive natural language answers.
Cultural Fit Analysis
The candidate's project diversity, ranging from a rideshare app to advanced AI/ML systems, indicates a broad interest and adaptability. Their involvement in a YC W25 startup (Wildcard AI) and a research lab (AIEA Lab) suggests an inclination towards innovative and challenging environments, which aligns well with a dynamic AI engineering culture. The academic projects also show initiative and a drive to apply theoretical knowledge to practical problems. However, the candidate is still pursuing their bachelor's degree, which might imply a need for mentorship and structured guidance in a professional setting.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through their project work, particularly in optimizing search and indexing processes. Their experience in architecting scalable systems and managing asynchronous workflows suggests good operational fit for roles requiring robust and efficient solutions. The leadership role in the UCSC Rideshare project indicates teamwork and project management potential. However, without specific psychometric or English test results, a comprehensive assessment of communication, stress handling, and team collaboration soft skills is limited.