Rao Akif

Education

Graduated: 2020

Graduated: 2022

Languages Proficient JavaScript (3 yrs) · TypeScript (2 yrs) Intermediate SQL (1 yr) · Python (2 yrs) Beginner Cypher (1 yr) · Pandas (1 yr)

Software AWS · GCP · Langchain · LangGraph · Docker · Kubernetes · TensorFlow · JupyterNotebook · Git · DVC · Bash/Shell

Sep 2024 - Present

HEADSTARTER

New York, NY

Built 14+ machine learning, AI-engineering, and full-stack projects in fast-paced software team environments
Developed 5+ neural networks in Python, 11 apps in Typescript on AWS/Vercel with dev and production environments
Implemented LLM-chaining, hyperparameter tuning, fine-tuning on 10+ LLM models controlling for latency & accuracy
Coached by Google Machine Learning, Google Kubernetes, Two Sigma, Tesla, Figma, and Citadel Engineers
Created 321+ commits on GitHub with 7-day deadlines, increasing Career Capital by 40% from start date

Dec 2023 - Jul 2023

Tekhliq Labs

London, UK

Developed an Urdu TTS system by fine-tuning NVIDIA Tacotron2 model, achieving an MOS of 3.38 with 2.5 hours of training data
Implemented the WaveGlow vocoder to enhance the naturalness and prosody of synthesized Urdu speech in low-resource settings
Applied data preprocessing and augmentation techniques to manage the Urdu speech dataset, improving model training efficiency
Collaborated on integrating transfer learning methodologies to adapt existing English TTS models for Urdu, reducing development time and computational resources

Aug 2023 - Sep 2024

Innovent Tech

Dubai, UAE

Developed robust full-stack applications for IoT-powered solutions using Node-RED and Node.js, enhancing asset management
Implemented dynamic back-end solutions to streamline data flow, enhancing user experience and reducing system latency
Integrated IoT devices with cloud services to enable real-time data analytics, improving decision-making processes
Collaborated with cross-functional teams to deploy scalable IoT apps, ensuring seamless device-application communication

Dec 2023

Developed an AI Search Engine using Next.js and TypeScript, enabling web scraping with Puppeteer and Cheerio
Implemented LLM-based chat interface with source citations, enhancing reliability and user engagement
Optimized performance with Redis-based rate limiting and middleware enhancements for scalable API handling

Dec 2024

Built a web app for generating images from text prompts using a model hosted on serverless GPUs
Utilized React, TypeScript, Modal, and APIs to create a robust image generation pipeline
Ensured low-latency performance (<2 seconds) for concurrent requests while scaling GPU resources effectively

Dec 2024

Built a system to find relevant stocks based on natural language queries such as 'What are companies that build data centers?'
Wrote a scalable embeddings script to add stock tickers in Pinecone for similarity searches
Created a FastAPI deployed on Render to generate text embeddings without additional dependencies
Enabled filtering by key metrics like market cap and volume for targeted stock searches
Integrated natural language processing for user-friendly stock query searches

Dec 2024

Created a full-stack web app with an interface for inputting prompts and viewing responses from multiple LLMs side-by-side
Integrated metrics such as accuracy, relevancy, and response time for evaluating different LLMs
Designed a database to store user prompts and experiment results with robust indexing and relational tables
Built an analytics dashboard for visualizing performance metrics and comparing different experiments

Oct 2024 - Present

Mar 2022 - Jul 2023

Sep 2022 - Mar 2023