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AI Engineer with less than a year in Generative AI and Image Generation Systems.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI-focused fresher with hands-on experience in Generative AI and image generation systems, skilled in building end-to-end AI solutions using LLMs, diffusion-based models, and prompt engineering. Strong understanding of GenAI workflows, model inference, and high-quality output generation, with a passion for creating user-driven AI applications.
Vignan's Lara Institute of Technology and Science
Bachelor of Technology · Electrical and Electronics Engineering
August 1, 2021 – June 30, 2025
AI POWERED IMAGE GENERATION SYSTEM (GENERATIVE AI)
January 1, 2025 – June 1, 2026
Designed and developed an AI-powered image generation system that creates anime, artistic, and cartoon-style images based on user text input. Implemented diffusion-based models to generate high-resolution 4K and 8K images, focusing on prompt engineering and output quality optimization. Built an end-to-end pipeline covering user input → prompt processing → model inference → image generation.
View ProjectPCAP: Programming Essentials in Python
Cisco Networking Academy
June 1, 2026 – Present
Oracle Cloud Digital Badges (Data Science and Generative AI)
Oracle Cloud
June 1, 2026 – Present
Oracle Cloud Infrastructure 2025 Certified Genarative AI
Oracle Cloud Infrastructure
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's project experience is focused on Generative AI, which aligns well with an AI Engineer role. The academic project demonstrates initiative and a passion for the field. The certifications further support this alignment. However, the lack of diverse project experience or team-based work in the provided data limits the assessment of broader cultural fit beyond technical alignment. The candidate is a fresher, which implies a learning-oriented mindset, potentially fitting into a growth-focused culture.
Soft Skills & Operational Fit
The candidate lists analytical thinking, creative problem solving, critical thinking, continuous learning, and attention to detail as soft skills. These are generally positive for an AI Engineer role, indicating a proactive and problem-solving mindset. However, without behavioral assessment data, the operational fit based on these self-reported skills is speculative.