Akash Rai

AI Researcher

Bengaluru, Karnataka, India1 yr 4 mos experience

AI EnabledAI ML Practitioner

Key Highlights

Intel Unnati Grand Challenge Finalist
Two-time IEEE Hackathon winner
Expertise in deep learning and NLP

Stackforce AI infers this person is a Machine Learning Engineer with a focus on AI solutions in defense and technology sectors.

Contact

Skills

Core Skills

Machine LearningDeep LearningNatural Language Processing (nlp)

Other Skills

Python (Programming Language)OpenAI SDKMongoDBDockerContinuous Integration (CI)LanggraphLangChainTime Series AnalysisLong Short-term Memory (LSTM)Deep Neural Networks (DNN)FastAPITensorFlowRetrieval-Augmented Generation (RAG)Next.jsFlask

About

As an AI enthusiast and aspiring Machine Learning Engineer, I have a passion for solving complex problems through innovative AI solutions. Currently, I have worked as an AI intern, where I contributed to the cutting-edge projects by the companies. I am an Intel Unnati Grand Challenge Finalist and a two-time IEEE Hackathon winner, continually striving to expand my expertise in deep learning and NLP.

Experience

1 yr 4 mos

Total Experience

1 yr 4 mos

Average Tenure

1 yr 4 mos

Current Experience

Inferigence quotient pvt ltd

AI Engineer

Feb 2025 – Present · 1 yr 4 mos · Bengaluru, Karnataka, India · On-site

Architected and deployed an end-to-end document intelligence system for Indian Navy, progressing from RAG-based report generation with grounded MongoDB data to production-scale LLM inference platform serving defense operations.
Deployed an on-premise microservices architecture (RabbitMQ, MongoDB, MinIO) with 5 containerized services and a LLM Inferencing Engine with docker-compose, implementing CI/CD pipelines (on Gitea and TeamCity) optimized for air-gapped defense environments.
Enhanced system capabilities through continuous pre-training of SLMs using PEFT techniques, achieving domain specialization for military documentation .
Designed a reliable report ingestion pipeline with on-device LLMs and rule-based methods for intelligent document understanding.
Delivered PoC projects for clients involving LLM integrations with social media platforms and developed chatbots with agentic capabilities using the OpenAI SDK.

Python (Programming Language)OpenAI SDKMachine LearningDeep Learning

Ai planet

AI Engineer Intern

Oct 2024 – Feb 2025 · 4 mos · Remote

Developing Multi-Agent architectural applications for assessment question generation with Langgraph and Langchain.
Developed components for GenAI Stack, AI Planet's drag-and-drop LLM pipeline builder by implementing modular functions for seamless workflow creation.

LanggraphLangChainMachine LearningNatural Language Processing (NLP)

Amazon

Amazon ML Summer School

Jul 2024 – Aug 2024 · 1 mo · Remote

Deep Dive on the concepts from ML/DL/RL and also NLP, from Industrial experts in Amazon.

Time Series AnalysisLong Short-term Memory (LSTM)Machine LearningDeep Learning

Deeplogic ai

AI Intern

Mar 2024 – Aug 2024 · 5 mos · Remote

Integrated a high-capacity custom RAG solution into backend infrastructure using FastAPI, replacing Vectara (RAGaaS) and achieving a 10x cost reduction while enhancing query retrieval through hybrid search capabilities.
Executed metadata migration from PineconeDB to MySQL, enhancing filtering capabilities and improving user experience during query processes.
Debugged and analyzed (performed EDA) on pipeline outputs at each stage to increase final result relevancy.

Python (Programming Language)Deep Neural Networks (DNN)Machine LearningDeep Learning

Intel corporation

Project Intern

Jun 2023 – Aug 2023 · 2 mos · Bengaluru, Karnataka, India · Hybrid

Built a project on fake news detection using BERT model and other deep learning techniques with an additional feature for detecting AI generated fake news also

Natural Language Processing (NLP)TensorFlowMachine LearningDeep Learning