Rahul P.
Backend AI Engineer with extensive hands-on experience in developing and deploying AI/ML solutions to enhance automation, decision-making, and business efficiency. Specializes in building and optimizing machine learning models, implementing deep learning frameworks, and deploying scalable AI systems. Strong expertise in integrating AI with platforms like Airtable to build intelligent, automated workflows using APIs, scripting, and no-code/low-code tools. Experienced in the entire development lifecycle, including requirement analysis, system architecture, implementation, debugging, and ongoing maintenance of software and AI-driven systems.
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Developed high-performance AI-powered backend systems utilizing OpenCV, GStreamer, and CUDA for real-time data processing and computer vision tasks.
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Designed and implemented LLM-based solutions integrated with vector stores, enabling customized and context-aware AI applications.
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Built and automated data workflows by integrating Airtable with backend services for streamlined project management and real-time data syncing.
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Developed custom APIs and scripts to connect Airtable with AI models, enabling dynamic data interaction and automated decision-making pipelines.
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Leveraged Airtable as a lightweight backend for prototyping and deploying scalable AI-driven tools and dashboards.
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Technologies: Python, Deep Learning, Machine Learning, CUDA, OpenCV, GStreamer, Vector Databases, Large Language Models (LLMs), Airtable, REST APIs applications.
- Tech Used: Deep Learning, AI, Machine Learning, Python, Gstreamer, CUDA
- Led the end-to-end development of AI/ML models, from research and prototyping to scalable deployment, ensuring high efficiency.
- Drove AI initiatives, mentored engineers, and collaborated with cross-functional teams to align AI solutions with business objectives, leveraging cutting-edge technologies.
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Designed voice-enabled agents using Dialogflow and TTS/STT systems to streamline customer interactions.
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Built GPT-powered chatbots with context retention and semantic search using LangChain and vector databases.
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Developed Agentic AI solutions leveraging AutoGPT for multi-step task automation, API integration, and intelligent decision-making.
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Applied prompt engineering and RAG architecture for scalable and accurate AI responses across business use cases.
- Skills: Community Outreach, Personal Branding, Artificial Intelligence (AI), Coaching, AutoGPT, Google STT & TTS, Prompt Engineering,
- Advised clients on AI/ML strategies, assessed business needs, and designed data-driven solutions to optimize decision-making and operational efficiency.
- Built, validated, and deployed machine learning models while ensuring scalability, performance, and alignment with industry best practices.
- Tech Used: Artificial Intelligence (AI), Generative Adversarial Networks (GANs), Multilingual NLP, IT Consulting
- Designed and developed various products, both independently and in teams.
- Built a custom chatbot for Dyme.earth. Developed data scraping tools that bypassed anti-bot systems on Google Ads and other websites.
- Worked on a cancer detection system using medical parameters and X-ray scans.
- Created chatgst.in, a full RAG system integrating GPT APIs and open-source models: Phi3. Deployed a machine learning app for Coca-Cola to detect coke in an India-based campaign.
- Worked on RASA framework for knowledge-based LLM to answer about the company concisely.
- Tech Used: Artificial Intelligence (AI), Automation, Retrieval-Augmented Generation (RAG), Full-Stack Development, Web Scraping
- Link: https://dyme.earth/
- Built and led a team of engineers and AI specialists to deliver high-performance software. Led the design of AI-powered apps, focusing on performance and scalability.
- Worked with C-suite to align tech initiatives with business goals.
- Managed projects from start to finish, ensuring on-time, on-budget delivery.
- Skilled in FastAPI, Django, Docker, MongoDB, Pinecone, and cloud-based AI solutions.
- Led R&D, integrating AI/ML advancements to stay ahead of the curve.
- Tech Used: Artificial Intelligence (AI), Computer Vision, Natural Language Processing (NLP), Multilingual NLP, Neuro-Linguistic Programming (NLP), Large Language Models (LLM), Predictive Analytics
- Developed expertise in vision-based technologies, including OpenCV, CUDA, PyTorch, Torchvision, YOLO, Tensor, and GStreamer.
- Collaborated with international teams to create AI-powered models.
- Built a GPT-powered application to deliver an AI-driven interactive bot for the company. Gained hands-on experience with no-code platforms like Airtable, Zapier, and Make.
- Tech Used: Deep Learning, Computer Vision, Artificial Intelligence (AI), Machine Learning, Python (Programming Language), Gstreamer, CUDA
- Developed and implemented LSTM, SARIMA, and ARIMA models to estimate revenue with an 88% accuracy rate for newly incorporated organizations.
- Designed and deployed chatbots for two distinct clients across different industries, enhancing customer engagement and automation.
- Engineered a data pipeline using the ELK stack, enabling real-time visualization of sales data, resulting in a 90% increase in productivity for a corporate client.
- Built a content-based recommendation system serving thousands of users for RamailoGames, improving user engagement and content discovery.
- Led backend development efforts for multiple community-driven platforms (e.g., Bookmark, Food-Busters) using Flask, ensuring seamless functionality for hundreds of users.
- Optimized shortest path-finding algorithms by 50% by applying Folium, Networks, and OSMnx, contributing to enhanced geospatial analytics.
- Gained hands-on experience in Docker, NGINX, and AWS cloud services over 4 months, strengthening cloud deployment and infrastructure management expertise.
- Tech Used: Machine Learning, ETL (Extract, Transform, Load), Python, Deep Learning, Natural Language Processing (NLP), SQL, Data Warehousing, Data Engineering, TensorFlow