Rao Akif

Education

Pakistan Institute of Development Economics, Islamabad

Graduated: 2020

Masters of Philosophy in Development Studies

Microverse Inc.

Graduated: 2022

Full Stack Web Development Program | 1 year

Skills

Languages   Proficient  JavaScript(3yrs)  ·  TypeScript(2yrs)   Intermediate  SQL(1yr)   ·  Python(2yrs)   Beginner  Cypher(1yr)  ·  Pandas(1yr)  
Software   AWS  ·  GCP  ·  Langchain  ·  LangGraph  ·  Docker  ·  Kubernetes  ·  TensorFlow  ·  JupyterNotebook  ·  Git  ·  DVC  ·  Bash/Shell

Experience

Software Engineering Resident

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

Software Engineer

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

Junior Software Engineer

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

AI Projects

AI Search Engine  |  (~30 hours) - GitHub Link

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

Pentagram: Realtime Image Diffusion  |  (~40 hours) - GitHub Link

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

Stock Analysis and Search Engine  |  (~50 hours) - GitHub Link

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

LLM Evaluation Platform  |  (~40 hours) - GitHub Link

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

Brain Tumor Classification  |  (~20 hours) - GitHub Link

Nov 2024 - Dec 2024

  • Used neural networks in Python to classify 1000 MRI scans into 3 types of brain diseases with a custom model
  • Generated multimodal MRI reports for neurosurgeons in under 200ms after image classification and training

Activities

AI Blogs @medium - Publish blog on Data Science, Machine Learning, AI Tuning, and Generative AI Trade-offs

Oct 2024 - Present

SWE Apprenticeship @colab - Complete Product Development experience in a Remote Team

Mar 2022 - Jul 2023

Code Reviewer @microverse - Performing code review of junior developers

Sep 2022 - Mar 2023