Vetted Keras Professionals

“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.”

“Hands-on technical/product-facing engineer with experience operationalizing LLM/agentic workflows and debugging them in real time using logs, traces, and metrics. Also supports go-to-market by running developer-focused live coding demos and partnering with sales on discovery and integration/maintainability concerns through clear technical documentation.”

“Full-stack engineer who built a lost-and-found pet management platform (React + Node/Express + SQL) with a focus on scalability (stateless JWT auth, modular REST APIs, cloud-based image handling) and performance (Artillery load testing, Chrome DevTools, query/index tuning). Also demonstrates systems-thinking around low-latency real-time voice pipelines integrating WebSockets, ASR, LLMs, and audio output, and has experience translating founder input into shippable product via rapid prototyping.”

“AI/ML practitioner with production experience building a RAG-powered contextual customer support agent, optimizing for low latency using vector databases and smaller LLMs. Also deployed a fraud detection model on Kubernetes with auto-scaling for heavy transactional loads, and improved chatbot accuracy by 15% through metric-driven testing and evaluation. Partners with Marketing on personalization/recommendation initiatives with measurable outcomes tied to customer feedback.”

“Built a solo full-stack equipment manager app for the game Dragon's Dogma, scraping a wiki with Beautiful Soup, transforming data to JSON, modeling armor/weapon schemas, and integrating everything into a PostgreSQL-backed API with caching. Dockerized and deployed the application to the web.”

“Robotics software learner building a self-directed recycling robot project in Isaac Sim, integrating ROS2 + Nav2 + SLAM with camera/LiDAR sensing and CV-based object detection. Has prior hands-on ROS2 work creating a YOLO detection node visualized in RViz and has built/optimized simulated line-follower and maze-solver robots in Webots, documenting progress publicly on GitHub and LinkedIn.”

“Built a production automated resume matching system using Python, FAISS vector search, and Selenium-based job scraping, including mitigation for IP blocking and heterogeneous site structures. Also develops LLM/RAG applications with LangChain, using Pydantic-guardrailed structured outputs and LLM-as-a-judge evaluation (including a project focused on tone/semantics for a 3D avatar’s emotional responses).”