Vetted Data Structures and Algorithms Professionals

“Autonomous robotics student who built an end-to-end ROS2 semantic goal navigation system as a solo course project, integrating CLIP-based vision-language understanding with SLAM Toolbox and Nav2 to execute natural-language commands in Gazebo/RViz. Also implemented and tuned an RRT planner from scratch in Python and uses Docker plus GitHub workflows for reproducible, tested robotics codebases.”

“Interned at Zonda where he built an AI-driven semantic search solution over ~280M housing/builder records. Iterated from local LLMs via llama.cpp quantization to a vector-embedding retrieval system, then boosted semantic accuracy with a custom spaCy NER layer and re-ranking, optimizing for latency through precomputation. Collaborated with economics-focused stakeholders to reduce manual document/paperwork time by enabling natural-language search over internal data.”

“Built and deployed an LLM + RAG + memory system on a Furhat social robot, adding continuous face/voice recognition embeddings over WebSockets to enable persistent, natural conversations across sessions. Experienced working around real-world hardware/latency constraints and uses Datadog plus structured debugging/rollback practices for stabilizing customer-facing LLM workflows.”

“Full-stack engineer with fintech and AI feature experience who shipped an AI-powered project summary module in Next.js (App Router + TypeScript) with secure server-side fetching and route handlers to a FastAPI backend, then owned monitoring and performance fixes in production. Demonstrated measurable UX wins (30% faster dashboard loads) and strong backend fundamentals (Postgres indexing/EXPLAIN ANALYZE, SQS-orchestrated idempotent reconciliation workflows with DLQs and retries).”

“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”

“Robotics software engineer with hands-on ROS2 autonomy experience across F1TENTH and Turtlebot platforms, building planning/control behaviors (Pure Pursuit, Follow-the-Gap, emergency braking, PID wall following) and validating in Gazebo/RViz. Also integrated a custom curvature-based speed planning node into Autoware (with AWSIM), demonstrating practical autonomy stack integration and strong debugging of LiDAR pipelines.”

“Completed an Amazon externship building a GPT-4 + RAG pipeline to summarize themes from hundreds of employee reviews for workforce analytics aimed at improving warehouse retention. Emphasizes production-readiness through labeled-data evaluation, source attribution for explainability, human-in-the-loop review, and rigorous data cleaning/observability to debug real-world LLM workflow issues.”

“Built and operated a production TypeScript backend for a stateful conversational quoting chatbot at Tringapps, orchestrating multi-step workflows and session state while integrating with Salesforce and NetSuite. Implemented validation/retry logic, modular architecture, and strong logging/observability to handle real-world edge cases and external API failures.”