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Vetted Teaching Assistants in Pennsylvania
Pre-screened and vetted in Pennsylvania.
Intern Software Engineer specializing in AI agents, RAG, and full-stack web development
Mid-Level Full-Stack Software Engineer specializing in FinTech and cloud-native AI systems
Kaustubh Rai
Mid-level Software Engineer specializing in distributed systems and cloud-native microservices
“Software engineer with ~2 years at UnitedHealth Group plus CMU coursework/TA experience, spanning backend modernization and cloud-native operations. Worked on migrating a customized open-source EDI system from Python 2 to Python 3 while improving SQLite database traceability via JSON exports, and has hands-on Kubernetes microservices deployment on Azure using Helm, HPA, and Jenkins-based Git-triggered CI/CD. Also built a large-scale real-time ride-hailing simulation using Kafka + Samza with explicit fault-tolerance strategies.”
Mid-level Machine Learning Engineer specializing in GenAI, forecasting, and MLOps
Shweta Chavan
Junior Computer Vision & ML Engineer specializing in autonomous perception systems
“LLM/RAG engineer who built a production-style multi-agent orchestrator for resume-to-recommendation workflows (PDF ingestion through screening and recommendations), emphasizing prompt tuning and strict JSON output contracts. Currently building a RAG application for an NGO using Airflow (DAGs + embeddings) and tackling messy, missing/imbalanced data; has hands-on retrieval stack experience (FAISS/HNSW, bge embeddings) and uses rigorous evaluation metrics for groundedness and hallucination control.”
KaMing Cheung
Junior Software Engineer specializing in full-stack and machine learning
“CMU IoT coursework project builder who implemented an end-to-end TinyML gesture recognition system on a Particle Photon + ADXL345, streaming data via MQTT/Node-RED to a real-time Node.js frontend and deploying a quantized logistic regression model on-device. Also explored multi-drone coordination, implementing leader-follower offset control and a pivot/arc turning strategy to avoid collisions, and brings practical Docker/Kubernetes plus CI/CD workflow experience from internships.”
Kaustubh Rai
Junior Software Engineer specializing in scalable distributed systems and cloud platforms
“Backend engineer with experience at UnitedHealth Group redesigning a high-traffic Spring Boot microservice from blocking to reactive architecture during peak season, cutting median latency by 47% for a service used by ~10M customers annually. Strong in Kubernetes-based deployment/scaling and pragmatic rollout strategies (blue-green/incremental traffic shifting) with performance and database troubleshooting.”
Intern Product Manager specializing in FinTech and AI-powered consumer apps
Senior NLP Research Scientist specializing in summarization, argument mining, and LLM evaluation
Junior Software Engineer specializing in AI/ML and cloud-native systems
Junior Full-Stack Software Engineer specializing in web platforms and algorithms
Saptarshi Sengupta
Mid-level NLP/LLM Researcher specializing in question answering and retrieval-augmented generation
“Built ToolDreamer, a framework for selecting relevant tools for LLM agents by training a retriever on LLM-generated reasoning traces, and has hands-on experience building multi-agent systems in AutoGen (MAG-V) focused on question generation and tool-trajectory verification. Currently works as an AI-guides supervisor at Penn State, regularly communicating AI concepts to non-technical stakeholders.”
Junior Product Solutions Engineer specializing in systems integration and AI tooling
Mid-level Computer Science PhD Researcher specializing in privacy-preserving sensing and HCI
Mid-level Software Engineer specializing in distributed systems and backend platforms
Mid-level Backend Software Engineer specializing in distributed systems and cloud-native microservices
Monil Patel
Junior Software Engineer specializing in backend and cloud systems
“Full-stack engineer with hands-on experience spanning analytics products and fintech infrastructure. Built a YouTube Data Aggregator end-to-end in 2025 with ingestion, dashboards, and predictive modeling, and also shipped Stripe webhook/payment systems at FinPay supporting $5M+ in transactions with 99.9% uptime.”