Vetted Research Assistants

“Backend/DevX engineer with startup experience who built internal JavaScript SDKs for POS integrations, including a daily GMV calculation feature standardized across multiple POS providers. Strong in performance debugging (used Jaeger to resolve legacy WebSocket bottlenecks) and developer enablement—built a cronjob migration tool (ArgoWorkflow to internal platform) with documentation that let teams migrate in ~30 seconds, plus handled on-call and internal support.”

“Enterprise customer success/implementation leader focused on AI-driven operational intelligence deployments in complex environments (e.g., large international airports). Has led end-to-end rollouts across 1200+ camera feeds and multiple airport systems, driving adoption stabilization within 90 days, influencing product roadmap (configurable alerts), and partnering with Sales to expand from initial congestion monitoring into additional operational modules.”

Subhash Chandra

Screened

Senior AI/ML & Robotics Research Engineer specializing in SLAM and multi-modal perception

Norman, OK8y exp

“Robotics engineer who built a smart campus tour robot on a Kobuki Turtlebot using ROS 1, implementing a full navigation stack (semantic world model, A* planner, tour executor, path follower) and integrating SLAM (gmapping) plus a hybrid reactive safety controller. Experienced taking systems from Gazebo simulation to real hardware, including extensive real-world debugging and Docker-based development to handle ROS/Ubuntu version constraints; planning a move to ROS 2 on Turtlebot 4.”

Jarin Tasnim

Screened

Staff/Lead Software Engineer specializing in distributed data and ML platforms

Mountain View, CA6y exp

“Defense-domain AI engineer who built a production ReAct-style RAG system for military training data/material generation, scaling to ~1000 users and cutting generation time by 50%. Also has experience designing GPU-cluster parallel computation with PyTorch and handling production incidents involving database performance and schema design.”

Shreyas Kumar

Screened

Entry-level AI Engineer specializing in LLMs and applied NLP systems

Syracuse, NY1y exp

“Built Lumo, a real-time voice AI companion, owning the product end-to-end across React/TypeScript, FastAPI WebSockets, and PostgreSQL. Stands out for combining deep full-stack systems thinking with voice UX polish, reliability instrumentation, and configurable parent-control guardrails in a multi-tenant setup.”

SUMANTH Metimath

Screened

Mid-level Data Scientist specializing in ML, LLMs, and AI systems

Potsdam, NY3y exp

“Candidate takes a pragmatic approach to AI-driven development, using AI as a productivity and learning aid while emphasizing personal understanding and code validation. They have hands-on experience applying AI-assisted workflows to a resume analysis and ATS scoring project, including code generation, debugging, parsing logic improvement, and testing.”

“Systems-oriented engineer with strong Python depth who repeatedly improves throughput in complex, ambiguous environments by designing pragmatic human-in-the-loop automation. Notable wins include a record-validation workflow that put a department over six months ahead of schedule and saved $500K+, plus AI-assisted and migration tooling integrated with Jama for engineering requirements and traceability.”

Sheng-Fang Chien

Screened

Junior Software Engineer specializing in full-stack development and ML systems

Blacksburg, VA4y exp

“Built a full-stack weather outfit web app feature set using React, TypeScript, Supabase, and PostgreSQL, including wardrobe management, personalized outfit recommendations, and image export. Demonstrates practical end-to-end ownership, from schema/query design to production debugging of CORS issues and performance improvements through client-side caching.”