Headline

AI Engineer | Machine Learning & Generative AI | LLM Fine-Tuning • RAG • Vector Search | Python Backend

About

Bangalore Institute of Technology BE candidate in Electrical, Electronics, and Communications Engineering with hands-on experience in AI and machine learning. Contributed to enhancing predictive accuracy of large language models (LLMs) by collaborating with cross-functional teams at mFilterIt and driving impactful fraud detection solutions. At Scale AI, supported AI model refinement for mathematical problem-solving and coding tasks, aligning outputs with customer needs. Proficient in Python, data preprocessing, and model evaluation, with certifications in data science and generative AI. Committed to leveraging AI for innovative and scalable solutions.

Location

Bengaluru

AI stack

antigravity

claude code

hugging face

langchain

n8n

openai

Work experience

Software Engineer at BrainerHub Solutions, Dec 2025 - Present · 9 mos, Ahmedabad, Gujarat, India, • Architect and maintain backend infrastructure for AI-powered SaaS applications using Python and FastAPI, enabling sub-200ms model inference response times in production. • Design RESTful APIs to expose ML pipeline endpoints, supporting model inference, vector search, and real-time data processing for multiple concurrent AI features. • Build scalable MLOps-aligned backend systems integrating LLM inference, embedding services, and retrieval components into unified application workflows. • Collaborate cross-functionally with product and AI research teams to translate model requirements into system architecture decisions and production deployment plans.

AI Engineer at Scale AI, Jan 2025 - Dec 2025 · 1 yr, Remote, • Improved AI model accuracy by 18% on coding and mathematical reasoning benchmarks by fine-tuning models using Python and C++, applying DSA-based optimizations and RLHF-style feedback loops. • Increased evaluation pipeline efficiency by 25% by engineering automated feedback and scoring frameworks in Python, using precision/recall and custom mathematics-based reliability metrics. • Developed structured prompt evaluation datasets and annotated training corpora to improve model instruction-following and reduce hallucination in code generation tasks.

Research And Development Intern at mFilterIt, Oct 2024 - Jan 2025 · 4 mos, Noida, Uttar Pradesh, India, • Enhanced predictive accuracy of Large Language Models (LLMs) by 30% through effective project management, addressing customer needs with tailored solutions using tools such as scikit-learn, pandas, NumPy, and TensorFlow. • Enhanced predictive accuracy by 25% through effective project management of data preprocessing, feature engineering, and model evaluation, mitigating project risks during the transformation process. • Collaborated with cross-functional teams to apply LLMs for fraud detection and data insights.

Education

Bachelor of Engineering - BE, Electrical, Electronics and Communications Engineering, Bangalore institute of technology

12th, Science, Delhi Public School - India

Public links

github: https://github.com/Spidy27

leetcode: https://leetcode.com/Spidy27