Wasey Mulla

Bioinformatics Engineer Intern @ Colossal Biosciences

About

I graduated from the University of Texas at Dallas with a Master’s in Computer Science, concentrating in Intelligent Systems, and a Bachelor’s in Computer Science.I am a Full-Stack and AI Engineer with experience building production software systems and integrating machine learning into real-world applications. My work spans backend API design, authentication and authorization systems, database integration, and cloud deployment, along with developing NLP systems, AI agents, and machine learning models embedded directly into user-facing products. I engineer end-to-end intelligent systems that combine scalable software architecture with applied AI. I focus on integrating machine learning models into scalable backend systems and user-facing applications.If you are working on scalable software or AI-driven products, I am always open to connecting and discussing new ideas!

Country

United States

City

Plano

Industry

Computer Software

Skill

TypeScript, Artificial Intelligence (AI), Prompt Engineering, Agentic AI Development, Retrieval-Augmented Generation (RAG), Continuous Integration and Continuous Delivery (CI/CD), Large Language Models (LLM), REST APIs, Applied Machine Learning, Biostatistics, Docker, Genetics, FastAPI, TensorFlow, Keras, Machine Learning, Big Data, Data Analysis, Data Science, React Native

Experience

Bioinformatics Engineer Intern

Colossal Biosciences

2025-9 - 2025-12 · 4 mos

Dallas, TX

• Performed single-cell RNA-seq analysis to identify gene expression patterns and distinct cell populations within biological datasets. • Applied unsupervised clustering (Leiden, K-means) and dimensionality reduction (PCA, UMAP) to visualize high-dimensional data. • Conducted diﬀerential expression analysis using Wilcoxon rank-sum tests to uncover key genes per cluster. • Automated RNA-seq and PIP-seq pipelines with Dockerized modules (FastQC, TPM normalization, PIPseeker), improving reproducibility and runtime consistency. • Visualized cluster-level gene expression patterns and biological pathways to support biologists in interpreting molecular diﬀerences across conditions.

AI Engineering Intern

HealthSci.AI

2025-1 - 2025-5 · 5 mos

• Deployed TypeScript AI agent for real-time engagement on X (Twitter) and Telegram, raising visibility of company updates. • Enhanced Eliza framework by creating multi-personality conversational agents, driving more natural and engaging interactions. • Built RAG pipeline with embeddings for context-aware search, boosting engagement by 70%. • Standardized Gitpod workflows for development/testing, streamlining collaboration and adding 1,000+ new social media followers.

Machine Learning Engineer Intern

INMO.AI

2024-5 - 2024-8 · 4 mos

Austin, TX

• Developed and deployed modular NLP microservices using Python, FastAPI, and Docker, enabling a scalable pipeline that processed over 50,000+ text inputs per day. • Integrated with Apache Kafka to enable real-time message streaming across distributed NLP services, reducing latency by 40%. • Designed RESTful APIs to serve NLP model outputs with lower latency, improving performance for downstream applications. • Collaborated cross-functionally to containerize services and deploy them to AWS, ensuring reliability, scalability, and security.

Software Engineer Intern

Atticus Capital

2022-5 - 2022-8 · 4 mos

United States

• Designed an investment portfolio mobile app with a user-friendly front-end interface using a Figma mockup, embodying consistent design principles and brand identity. Simplified user data visualization for enhanced accessibility and comprehension. • Led the development of a cross-platform mobile application using React Native, JSX, Tailwind, and Expo, optimizing performance for a responsive user interface. • Seamlessly integrated the mobile application with an API, enabling users to access and update mobile application content, boosting engagement and satisfaction. • Implemented a secure authentication system and connected the application with MongoDB to efficiently store and manage vital user investment information, ensuring data integrity and accessibility.