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Vetted Research Assistants
Pre-screened and vetted.
Mid-level Software Engineer specializing in AI agents, RAG, and test automation
Junior Robotics Engineer specializing in autonomy, SLAM, and model predictive control
Junior Robotics Engineer specializing in autonomy, simulation, and 3D perception
Entry-Level Robotics Research Assistant specializing in autonomous systems and reinforcement learning
Principal/Lead Data Engineer specializing in large-scale pipelines, NLP, and graph databases
Junior Design Engineer specializing in product design, UX systems, and creative AI tools
Mid-level AI/ML Engineer specializing in Generative AI, MLOps, and geospatial intelligence
Junior Machine Learning Engineer specializing in computer vision and LLM applications
Mid-level Full-Stack Software Engineer specializing in FinTech microservices and event streaming
Mid-level AI Engineer specializing in agentic GenAI and cloud MLOps
Intern Full-Stack/AI Software Engineer specializing in cloud serverless and LLM systems
Mid-level Computer Science PhD Researcher specializing in privacy-preserving sensing and HCI
Mid-level Autonomy Engineer specializing in robotics perception and sensor fusion
Junior Software/ML Engineer specializing in cloud platforms and applied machine learning
Junior Robotics & ML Engineer specializing in computer vision and transformer models
Mid-level Data Scientist specializing in GenAI, NLP, and recommendation systems
Junior Robotics & AI Engineer specializing in SLAM, motion planning, and sim2real learning
Mid-Level Full-Stack Software Engineer specializing in modern web apps and microservices
Anshul Joshi
Mid-Level Software Engineer specializing in distributed systems and GenAI
“Capgemini engineer with 4+ years building and deploying high-availability, low-latency fraud detection APIs and multi-cluster distributed systems for a Fortune 20 bank, including zero-downtime production rollouts and multi-layer (SQL/network/hardware) performance debugging. Also built a Python + OpenAI/LangChain LLM-powered grading workflow for Austin School for Women, cutting feedback time from 90 minutes to 5 minutes per submission for 200+ learners.”
Srijan Dokania
Junior Robotics & Machine Learning Engineer specializing in perception, SLAM, and edge AI
“Built and deployed an Azure-based, fine-tuned CLIP visual retrieval system at Staples for a ~300k-item product catalog, improving edge-case recall by 12% by engineering a custom delta-similarity/dynamic-margin loss. Also has robotics experience using ROS2 for sensor/compute orchestration, including GPS-time-synchronized sensor triggering for robot swarms and latency-bounded optical-flow benchmarking for edge deployment.”
Naga Karumuri
Mid-Level Full-Stack Engineer specializing in AI and 3D computer vision
“Built and productionized an LLM-driven document verification workflow for a construction firm’s submittals process, moving from a Vercel/Next.js prototype to a FastAPI + LangChain/LangGraph backend with background workers and multi-server deployment. Uses LLM tools (e.g., OpenAI Codex/Cloud Code) for rapid development and log-driven root cause analysis, and partners with customer teams on evaluation metrics and iterative improvements.”