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Vetted Research Assistants
Pre-screened and vetted.
Junior Software Engineer specializing in Java game server plugins and machine learning
Junior Math & Computer Science Tutor and Researcher specializing in computational geometry
Director of AI & Technology specializing in enterprise AI transformation and full-stack web platforms
Junior XR/Unity Developer specializing in AR/VR/MR and interactive 3D systems
Senior Data Scientist and ML Engineer specializing in NLP, LLMs, and AI systems
Mid-level Software Engineer specializing in full-stack data systems and cloud automation
Junior Full-Stack Software Engineer specializing in web, mobile, and AI-enabled collaboration tools
Junior Machine Learning Engineer specializing in LLM agents, knowledge graphs, and multimodal AI
Junior Software Engineer specializing in AI-driven full-stack and distributed systems
Junior Full-Stack Software Developer specializing in web and cloud applications
Junior Full-Stack Developer specializing in web apps, APIs, and AI integrations
Junior Machine Learning Engineer specializing in deep learning and healthcare AI
Mid-level Backend Software Engineer specializing in AI-powered microservices and cloud infrastructure
Mid-level Sourcing & Supply Chain Analyst specializing in procurement analytics and cost reduction
Senior Full-Stack Product Engineer specializing in AI, Cloud, and regulated domains
Mid-level Software Engineer specializing in AI, backend systems, and full-stack development
Maneesh Ujji
Junior Machine Learning & Data Science professional specializing in AI agents and applied ML
“IT Analyst/research background with hands-on experience deploying and hardening a multi-agent AI support/triage system (ticket ingestion + knowledge-base retrieval) with strong emphasis on reliability and observability. Has debugged real production issues spanning backend services and network latency (sync failures/partial writes) and is comfortable in Linux environments; also has academic exposure to robotics simulation and ROS2.”
Priyank Jhaveri
Junior AI/ML & Mobile Engineer specializing in LLMs, synthetic data, and React Native
“Currently at Uplift AI shipping production LLM features that generate personalized growth insights from user reflections using BERT + embeddings + RAG, with strong safety/guardrail practices for sensitive contexts. Also built an end-to-end React Native UGC challenge submission/moderation system that improved repeat submissions and 7-day retention, and has applied rigorous clinical-style evaluation methods on a dental X-ray disease detection project to reduce false negatives.”
Abhish Khanal
Senior Robotics Researcher specializing in Embodied AI and learning-augmented planning
“Robotics software engineer with experience spanning safety-critical embedded medical hardware (low-cost neonatal baby warmer with PID temperature regulation) and advanced multi-robot planning research (belief-space planning with abstraction + MCTS to handle uncertainty). Strong ROS/ROS2 practitioner (Nav2/SLAM Toolbox/MoveIt) who builds custom packages (e.g., Insta360 panoramic imaging) and is hands-on debugging real robots from SLAM/frontier exploration to multi-robot collision avoidance and real-time performance.”
VenkataRamireddy Gaddam
Junior IoT/Embedded Systems Engineer specializing in ROS 2, LoRa, and sensor fusion
“Robotics/embedded developer with hands-on ROS 2 and micro-ROS experience on ESP32, building a remote-controlled high-power LED system. Worked across power distribution (buck-boost constant 30V), sensor calibration with real-time data checks, and long-range WiFi connectivity using an omnidirectional antenna achieving 100m+ coverage.”