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AI Engineer with 2+ years in Generative AI, LLMs & Computer Vision
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Assessing your cultural and operational fit
AI/ML Engineer with 2 years of experience building practical Al solutions across Generative AI, LLMS, RAG, Computer Vision and Edge Al. Skilled in developing, fine-tuning, and deploying Al models on both cloud and edge platforms, with a strong focus on performance and efficiency. Experienced in taking projects from research and prototyping to production, delivering scalable and reliable Al systems that solve real-world problems with low latency and high usability.
Gokaraju Rangaraju Institute of Engineering & Technology (GRIET)
Bachelor of Technology · Electronics and Communication Engineering
August 1, 2020 – June 30, 2024
Vintillix Global Innovation Private Limited
AI / ML Engineer
September 1, 2024 – Present
Hyderābād, Telangana, India
QuantumEco
Software Developer
July 1, 2024 – September 1, 2024
Chennai, Tamil Nadu, India
Tiny Language Model | Build Language Model from Scratch
June 23, 2026 – Present
Designed and developed a compact educational language model (LLM) for children's learning applications, enabling personalized tutoring, interactive storytelling, and age-appropriate question answering. Leveraged AWS SageMaker (p3 GPUs) for large scale pretraining and Amazon Bedrock for synthetic data generation. Built and optimized end-to-end data pipelines, instruction tuning workflows, and model evaluation frameworks. Fine-tuned the model through supervised fine tuning (SFT) on g4dn.xlarge instances, improving instruction adherence, conversational consistency, and educational relevance.
Child-Adaptive Educational AI Assistant (LLM + RAG)
June 23, 2026 – Present
Fine-tuned an open-source LLM using GRPO on custom robot-child interaction data and built educational RAG pipelines with FAISS and LangChain over curated Science and Social Science content, enabling safe, context-aware, age-appropriate, and curriculum-aligned responses for deployment on edge hardware.
Cultural Fit Analysis
The candidate's projects and experience demonstrate a strong alignment with an AI Engineer role, particularly in areas of Generative AI, LLMs, and Edge AI. The diversity of projects, from building a language model from scratch to developing child-adaptive AI assistants and optimizing inference on constrained hardware, indicates a broad interest and capability in the AI domain. The experience with both cloud and edge deployments suggests adaptability to various technical environments. The candidate's focus on performance optimization and real-world applicability aligns well with a results-oriented culture.
Soft Skills & Operational Fit
The candidate's resume highlights a strong focus on problem-solving, efficiency, and delivering scalable/reliable AI systems, which are critical for operational fit in a senior AI Engineer role. The project descriptions indicate an ability to take initiatives from research to production. However, without specific assessment data on soft skills, a comprehensive evaluation of collaboration, leadership, and communication in a team setting is not possible.