Vetted Llama Professionals

“Enterprise/industrial UX designer focused on making complex, real-time automated systems feel trustworthy and predictable. Has hands-on experience observing operators in logistics/automation environments, building shared interaction models to unify fragmented products, and collaborating tightly with engineers using component-system thinking (HTML/CSS/TypeScript) to ship resilient UIs that handle partial failures.”

“Backend/data engineer focused on climate/emissions data platforms, building production Python (FastAPI) microservices and AWS serverless/ETL pipelines (Glue/Athena/Lambda/EventBridge). Demonstrated strong reliability and observability practices plus measurable optimization wins, including cutting PostgreSQL query runtimes from minutes to seconds and reducing AWS costs from ~$6k/month to ~$400/month.”

“Research Analyst at Syracuse who deployed an LLM-powered lab automation system allowing researchers to run QCoDeS instrument workflows via natural language, with strong safety guardrails for real instruments and multi-instrument support. Also collaborated with non-technical stakeholders at iConsult on an audio classification/recommendation pipeline, translating business goals into metrics and Tableau dashboards with model comparisons and A/B test results.”

“Robotics software engineer who built an end-to-end system ("justmatrix"), focusing on multi-agent orchestration and a multi-RAG retrieval backend/API. Has hands-on ROS experience, including a custom node for reliable high-frequency sensor data routing, plus deployment automation using Docker, Kubernetes, and CI/CD.”

“Built a production LLM fine-tuning pipeline for domain-specific code generation at Pigeonbyte Technologies, including automated collection and rigorous quality filtering of 10M+ code samples (AST validation, sandbox execution/testing, deduplication, drift monitoring, and human-in-the-loop review). Also implemented end-to-end ML orchestration in Apache Airflow with data quality gates, dataset versioning in S3, benchmarking, and automated model promotion, and has a reliability-first approach to agent/workflow design.”

“Built and deployed a production bilingual (Bengali/English) AI virtual assistant that replaced IVR for telecom customer service at massive scale (~15M users), integrating ASR/TTS, Rasa dialogue management, and custom NLP. Overcame low-resource Bengali data and noisy call-center audio with synthetic data augmentation and transformer fine-tuning, achieving significant production gains including ~50% reduction in support calls.”

“Built and deployed a production LLM-powered recruitment chatbot that automates key recruiting steps (sourcing, candidate engagement, screening). Strong in agent orchestration with LangGraph, including guided graph-based workflows, context-aware routing, and reliability measures like clarifying steps plus human-in-the-loop evaluation.”

“Built and shipped a production-grade RAG-powered news summarization and Q&A product, tackling real-world issues like retrieval drift, hallucinations, latency, and autoscaling deployment (Docker + FastAPI + Streamlit Cloud). Experienced in end-to-end ML/LLM workflow automation using Airflow, Kubeflow Pipelines, and MLflow, and has demonstrated business impact (40% inference precision improvement) through close collaboration with non-technical stakeholders at Evoastra Ventures.”