Vetted Teaching Assistants in the Bay Area

Parth Tusham

Screened

Intern Software Engineer specializing in systems, cloud, and security

Sunnyvale, CA1y exp

“Systems and infrastructure engineer pivoting toward robotics software; brings strong low-level debugging, multithreaded systems, and networking experience where correctness and timing matter. Has hands-on experience using Docker and CI/CD to build reproducible test/evaluation environments (thesis), and proposes a disciplined, contract-driven approach to distributed communication and real-time performance debugging.”

Prajit Mohan

Screened

Junior QA Engineer specializing in test automation for web applications

Oakland, CA3y exp

“QA automation engineer with healthcare web experience who owned an end-to-end automated test suite (Java/Cucumber/Selenium and Cypress) and integrated it into CI/CD (Jenkins to GitHub Actions, qTest DoD gates). Known for boosting regression coverage to ~93%, stabilizing flaky Cypress tests, and catching production-impacting pipeline/environment redirect issues through workflow updates and cross-browser/regional scenario testing.”

Manaswini Gogineni

Screened

Junior Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Full-stack/platform engineer who has owned real-time analytics products end-to-end and built scalable TypeScript/React + Node.js systems using event-driven and microservices architectures (Kafka/RabbitMQ). Also created a widely adopted Go CLI that standardized AWS/Terraform provisioning across multiple teams, cutting environment setup from days to minutes through opinionated defaults, documentation, and cross-org partnerships.”

Alp Komban

Screened

Junior Machine Learning Engineer specializing in computer vision for medical imaging

Mountain View, CA2y exp

“Applied ML/LLM practitioner working in healthcare-facing products, using RAG and LoRA fine-tuning on medical data and implementing production monitoring (confidence scoring) for clinician oversight. Has hands-on experience debugging agentic/LLM pipelines (including OCR preprocessing fixes) and regularly delivers technical demos to doctors, investors, and conferences—contributing to adoption and even helping close a funding round through end-to-end pipeline walkthroughs.”

Aashna Kunkolienker

Screened

Junior AI Engineer specializing in agentic workflows and ML platforms

San Ramon, CA2y exp

“Building a production LLM/agent system for a leading US dental provider that extracts rules from payer handbooks/portals and EDI 271 responses to validate and improve patient cost estimates. Combines GCP stack (BigQuery, GKE, Cloud Run, Pub/Sub, Vertex AI) with strong agent reliability practices (observability, validator agents, grounding, PII/hallucination guardrails, confidence scoring) and has led non-technical customer stakeholders on enterprise ServiceNow↔Aha sync and AI-powered enterprise search/summarization.”

Zuocheng Li

Screened

Entry-Level Software Engineer specializing in full-stack web and Android development

San Jose, CA0y exp

“Early-career developer whose experience comes from classroom projects but has completed full end-to-end web app delivery: implemented login/search/favorites, integrated external APIs, and deployed to Google Cloud for multi-device use. Demonstrates user-centered iteration by recruiting friends to test and provide feedback, and has hands-on production-style debugging experience (e.g., resolving CORS issues during deployment).”

Bernie Miao

Screened

Junior Full-Stack Software Engineer specializing in EdTech and AI-powered learning tools

Berkeley, CA2y exp

“Edtech/education-focused engineer who took an accessibility-critical LLM/vision feature from concept to production: built an OpenCV-gated whiteboard capture pipeline feeding Gemini Vision for handwriting-to-LaTeX, improving math transcription 80% while cutting inference costs 60%. Also built RAG observability and retrieval fixes that stabilized inconsistent answers, and partnered directly with sales to reshape demos and open a new K-12 revenue pipeline aligned to California Digital Divide grant requirements.”

“Software engineer with hands-on embedded/robotics coursework experience (Arduino sensor integration and input handling built from scratch without external libraries) and strong DevOps/engineering productivity impact at work, including leading a CI/CD enhancement that runs only impacted tests to catch issues before PR approval.”

Darshi Jain

Screened

Mid-level Customer Success Manager specializing in ads, product strategy, and analytics

San Francisco, CA4y exp

“Revenue-focused seller with experience at Amazon and Vedanta, combining data-driven prospecting, account expansion, and GTM process building. Stands out for turning performance insights into repeatable growth motions—driving $3.1M annual revenue uplift and 40% format adoption at Amazon, while also building new-market playbooks from scratch in high-ambiguity industrial segments.”

Krishna Kodur

Screened

Mid-level Robotics & AI Researcher specializing in human-robot interaction and reinforcement learning

Santa Clara, CA8y exp

“Robotics software engineer who built an end-to-end mobile manipulation platform (Franka Panda on a Clearpath Ridgeback) for a simulated-kitchen human-robot interaction study with natural speech commands, implemented in Python/ROS. Has hands-on experience integrating diverse sensors (RealSense, LiDAR, biosignals) with deep learning frameworks (PyTorch, Hugging Face) and fine-tuning GPT-Neo, plus simulation (Gazebo) and modern deployment practices (Docker/Kubernetes, CI/CD).”

“Software engineer who owned end-to-end delivery of customer-facing agricultural forecast reporting (crop yield/health) and iterated quickly via rigorous edge-case testing and customer feedback. Also built an internal ML training platform (TypeScript/React + Flask/Python + MongoDB) used by every developer, with architecture designed to stay responsive under heavy compute load.”