Vetted Research Assistants in the Los Angeles Metro

“Built and operated a real-time multiplayer card game end to end, with hands-on ownership of frontend, backend, persistence, and production stability. Demonstrates strong systems thinking around concurrency, idempotency, and extensible architecture, including refactoring a tightly coupled PvP game into a modular engine that could also support bot players.”

Utkarsh Gupta

Screened

Junior Robotics & ML Engineer specializing in perception, navigation, and VLA models

Los Angeles, CA1y exp

“Robotics software engineer with hands-on AGV/AMR experience at ERIC Robotics, building ROS2-based LiDAR perception and localization on NVIDIA Jetson for real-time deployment. Improved unstable localization in challenging environments (e.g., tunnels/bushes along rail tracks) via scan-matching, filtering, and consistency checks, and cut latency by moving from rclpy to rclcpp and leveraging CUDA. Comfortable across the stack from simulation (MuJoCo/Isaac Sim/Gazebo, domain randomization) to deployment tooling (Docker, basic CI) and distributed ROS2/DDS systems.”

“Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.”

“AI/LLM engineer who built a production autonomous GenAI content ecosystem that generates short-form scripts, extracts viral highlights from long-form video, and dubs content into 33+ languages. Focused on making LLM outputs production-safe via schema enforcement, token-to-time alignment, critic-agent verification, and scalable async orchestration—cutting manual workflows by ~90% and saving $200k+ annually.”

“Built across data, backend, analytics, and visualization-heavy applications, including a nonprofit financial forecasting app, large-scale insurance model analysis at Mercury Insurance, and a publicly deployed soccer analytics dashboard. Stands out for combining machine learning, large-dataset SQL work, and practical production improvements like cutting dashboard load times to under two seconds and refactoring codebases for smoother team handoff.”