Vetted Matplotlib Professionals

“Backend/cloud engineer from Resilient Tech with hands-on experience deploying REST APIs and database migrations into a live ERP used by real customers while maintaining 99% uptime. Has debugged intermittent AWS container timeouts down to security group/load balancer misconfigurations, and has extended Python in an ERPNext system to meet GST/e-invoicing compliance requirements with strong customer collaboration.”

“LLM/agent systems builder who deployed a production hybrid router for immerso.ai that dynamically selects retrieval vs reasoning vs generative pathways, achieving an 82% factual-accuracy lift. Deep hands-on experience optimizing local Mistral 7B inference (4–5 bit GGUF quantization, KV-cache reuse) and building reliable RAG/agent workflows with LangChain/LangGraph/AutoGen across GCP Cloud Run and AWS (ECS/Lambda).”

“Built and deployed a production generative-AI copilot at Tungsten that automates invoice/form extraction template creation, reducing weeks of manual model-building work. Combines fine-tuned LLMs (PyTorch/HuggingFace) with OpenCV layout grounding to reduce hallucinations, and runs an end-to-end Kubeflow-based MLOps pipeline with drift monitoring, canary releases, and automated retraining.”

“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”

“Union College robotics graduate with hands-on ROS experience building an independent “waiter bot” that took spoken orders (Mozilla DeepSpeech), used OpenCV, and navigated via SLAM on a TurtleBot with LiDAR. Also led the Union College Robotics crew for four years and implemented PID control for micromouse maze robots; has additional software deployment experience with Dockerized FastAPI and CI/CD from coursework.”

“New grad who shipped an LLM-powered writing app (“Write-it”) to production on Azure with CI/CD (GitHub Actions + JFrog) and implemented an unconventional RAG pipeline to prevent repetitive prompts using embeddings and cosine similarity. Also participated in a Luma AI image/video generation hackathon, iterating with artist feedback and improving usability by rewriting non-technical prompts via an LLM.”

“Undergraduate AI/robotics research assistant who built a city-scale robotics simulation stack for embodied question answering, including JSON-driven environment generation and a ROS 2 pipeline bridging Isaac Sim sensors (CV/LiDAR) to external ML/RL algorithms. Also created and deployed an open-source library workflow tool adopted across multiple local libraries, using GitHub Actions CI/CD for signed releases and automated updates.”

“Backend engineer with experience modernizing legacy systems and building modular Python/Flask services, including a REST-to-GraphQL migration for an e-commerce platform that improved API response time by 45%. Strong in performance and scalability work across PostgreSQL/SQLAlchemy (indexing, JSONB, N+1 fixes, connection pooling) and high-throughput systems (Celery + Redis), plus integrating ML microservices with TorchServe, Kafka streaming, feature stores, and Prometheus/Grafana monitoring.”

“Frontend-focused engineer with startup experience (SmartPath, OPC AI) who owned and evolved an internal React/TypeScript component library treated like OSS—refactoring core form and API wrapper modules for stability, type safety, and smaller bundles. Comfortable diagnosing production issues via logs/API traces and shipping end-to-end fixes with tests and documentation, including internal workshops to drive adoption.”

“Built and productionized an LLM-powered customer support system using a RAG architecture with structured document ingestion, embedding retrieval, and prompt templates for product-specific grounding. Experienced diagnosing live agent/workflow failures (e.g., retrieval regressions after new docs) by refactoring ingestion/chunking and adding grounding constraints plus evaluation benchmarks. Also supports go-to-market by joining discovery calls, shaping MVP workflows into demos/prototypes, and creating post-launch documentation to drive adoption.”

“Robotics software engineer who built a ROS 2 Humble autonomous hospital-equipment detection/localization robot end-to-end in Gazebo (custom worlds/models, Nav2 waypoint navigation, YOLOv8n perception, TF2-based depth fusion) and solved real-time integration issues via multithreading and QoS tuning. Also implemented and tuned an MPPI controller to enable smooth reverse parking on an OpenPodCarV2 platform, including real-world reverse engineering and hardware/software debugging.”

“Backend engineer (Encore) who led the evaluation and redesign of a high-volume, low-latency real-time retrieval/ranking and inference platform on AWS, shifting from tightly coupled services to a modular architecture for better fault isolation and independent scaling. Strong focus on production reliability, observability, and security (JWT/RBAC, multi-tenant scoping, Postgres/Supabase RLS), with disciplined migration playbooks (feature flags, shadow traffic, dual writes/reconciliation).”

“Backend engineer who has led redesigns and migrations for a real-time logistics platform, improving scalability and resilience while managing eventual consistency tradeoffs. Demonstrates strong distributed-systems rigor (idempotency, transactions, async queues, monitoring) and builds secure, versioned FastAPI APIs with JWT/OAuth2, RBAC, and database row-level security.”

“Master’s thesis engineer who built and deployed a continuous real-time perception + state estimation + control loop under tight latency constraints, owning both software architecture and hardware integration. Strong ROS 2 fundamentals with a systems-first approach—stabilizes robotic behavior by instrumenting, logging/replaying real data, and fixing timing/synchronization issues rather than treating failures as purely algorithmic.”

“Built and deployed a production-grade LLM agent for credit management and accounts receivable automation, integrating ERP/MySQL data via a RAG pipeline and exposing services through FastAPI with Pydantic-validated outputs on AWS Bedrock. Emphasizes reliability and compliance for financial operations using schema validation and human-in-the-loop review, reporting ~32% reduction in manual work and ~41% improvement in response time/reliability.”

“Built and deployed a production AI-powered personalized learning platform (Django + FastAPI) featuring an LLM+RAG tutoring assistant and automated grading. Demonstrates strong applied LLM reliability engineering (structured JSON outputs with Pydantic validation, hallucination control via FAISS-based RAG thresholds and refusals) plus scalable async microservice design and Airflow-orchestrated ETL across AWS/GCP.”

“Built a production-style AI meeting summarization and action-item extraction system (Azure Speech-to-Text + transformer summarization/NER) exposed via a Flask REST API, with explicit guardrails to prevent hallucinated tasks. Strong focus on reliability: modular agent/workflow design, precision-first evaluation with human-validated golden notes, and practical orchestration patterns (tool-augmented agents; ready to scale into Airflow/LangGraph/Prefect).”

“Backend-leaning full-stack developer (Java/Spring Boot, Angular, MySQL) who emphasizes rapid iteration with quality via clean code, validation, and API testing. Built a web application to help women connect directly with NGOs, focusing on an intuitive dashboard and user walkthroughs to support adoption, and designed flexible REST APIs to handle frequent requirement changes.”

“Robotics software engineer with thesis work optimizing the Autoware perception pipeline via DDS/synchronization tuning for lower latency and better throughput, plus hands-on ROS1/ROS2 experience deploying perception (YOLOv8) and SLAM/localization on real vehicles and delivery robots. Has practical debugging depth (Kalman filter crashes, transformation/scan-matching issues) and CI/CD automation experience with Jenkins.”

“Co-op engineer who owned and shipped a Python/Flask backend for automating architecture reviews and system metadata processing, including ingestion from multiple internal APIs, RBAC, testing, and deployment. Has hands-on Kubernetes + GitOps (ArgoCD) experience, built Kafka-based real-time ingestion, and supported a cloud-to-on-prem migration with phased cutover, smoke tests, and performance tuning.”

“Built a production AI-powered university marking system that automates question generation and grading from PDF course materials using a RAG pipeline (S3 + Pinecone) orchestrated with LangChain/LangGraph and deployed on AWS ECS via Docker/ECR and GitHub Actions CI/CD. Addressed a key real-world LLM challenge—grading consistency—by implementing rubric-based scoring, retrieval re-ranking, and standardized context summarization, validated against human instructors.”

“AI/LLM engineer who built and deployed a production healthcare RAG chatbot ("DoctorBot") with strict medical safety guardrails, an 85% confidence-gated verification layer, and latency optimizations that cut responses from ~8s to ~2–3s. Also worked on finflow.ai to generate finance/banking test cases from BRDs, collaborating closely with non-technical domain stakeholders, and has hands-on orchestration experience with LangChain/LangGraph and agentic evaluation/monitoring practices.”

“Frontend-leaning engineer who shipped an end-to-end map-based discovery feature in a React Native mobile app, integrating location-based REST APIs with strong UX polish (loading/empty/error states) and cross-platform performance fixes. Also has experience building a Python backend with JWT auth and layered service structure, plus prior infrastructure work setting up centralized logging and monitoring.”

“Unity/VR developer who shipped a Meta Quest 2 immersive 360 training experience for Staffordshire Police as a solo programmer, including biometric gaze/reaction tracking and real-time data capture to an HTTP endpoint. Also building a Tomb Raider-like sci-fi adventure demo (Nexus 7) featuring FSM-driven character logic, motion-capture animation, custom controller optimization, and spline-following AI movement.”