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Vetted Graduate Research Assistants in New York
Pre-screened and vetted in New York.
Junior Software Development Engineer specializing in AI/ML and distributed systems
Executive CTO and product leader specializing in enterprise AI/ML and digital transformation
Mid-level Data Scientist/ML Engineer specializing in LLMs, NLP, and recommender systems
Junior Robotics & Controls Engineer specializing in UAV autonomy and embedded systems
“Robotics software engineer focused on autonomous drones and mobile robotics: implemented a sliding mode inner-loop controller and a RealSense T265 VIO state-estimation pipeline integrated into ArduPilot EKF3 for GPS-denied indoor flight. Strong simulation-to-deployment experience (Gazebo/MAVROS to firmware), ROS2 networking/debugging, and hands-on validation through multi-sensor trials and log analysis.”
Director of Intellectual Property specializing in technology transfer and deep-tech licensing
Jiyang Wu
Junior Software Engineer specializing in cloud microservices and database systems
“Grad student who co-developed a safety-oriented mental health LLM consulting agent using RAG + Gemini and Hugging Face emotion detection to assess user crisis level and adapt responses. Implemented a key reliability improvement for CRISIS scenarios by bypassing generative output and returning direct, emotionless, knowledge-base guidance to seek immediate real-world help.”
Junior Robotics Software Engineer specializing in autonomous systems and sensor fusion
Junior Backend/Systems Engineer specializing in distributed systems and security
Jeet Choksi
Mid-level Machine Learning Engineer specializing in real-time AI and data platforms
“ML/NLP engineer who has built production systems end-to-end: a real-time recommendation platform (100k+ profiles) using BERTopic-style clustering and a RAG-based news summarization/recommendation stack with ChromaDB. Strong focus on scaling and reliability (GPU batching, Redis caching, Kafka ingestion, Docker/Kubernetes, Prometheus/Grafana) and on maintaining model quality over time via drift monitoring and retraining triggers.”