Ceddy Muhoza

- Championed the development of an advanced LLM utilizing TensorFlow and PyTorch. - Personally, I find the dynamic adaptability of RNNs, especially LSTM networks, fascinating for their ability to capture temporal dependencies in text data, which was pivotal in enhancing our real-time financial news analysis, leading to a 35% improvement in trade decision accuracy. - Crafted and fine-tuned algorithmic trading strategies, employing a combination of CNNs for pattern recognition in market data and Gradient Boosting machines for their robust predictive capabilities. - My preference leans towards Gradient Boosting for its efficiency and effectiveness in handling varied data types, contributing to a 20% increase in annual ROI for our high-frequency trading portfolios. - Led the initiative to containerize ML models using Docker and Kubernetes, advocating for their use due to their unparalleled flexibility and scalability, which significantly boosted our deployment efficiency on cloud platforms like AWS. - Implemented a real-time data ingestion and processing pipeline using Apache Kafka, valuing its reliability and performance in streaming data scenarios, which is crucial for maintaining the low latency of our trading signals. Tech used: Kubernetes / Helm, Digital Ocean, Couchbase, Redis, Go, TypeScript, NodeJS, ReactJS, React Native, Storybook, Cypress, Jest, Mocha/Chai, GraphQL, Github Actions, ML, OAuth 2, Stripe, PayPal, TensorFlow, PyTorch, Keras, NLTK, Scikit-learn, Pandas, NumPy, SciPy, Matplotlib, Seaborn, Spacy, Apache Kafka, Apache Airflow, Docker, Kubernetes, Hadoop, Git, Jupyter Notebooks

• Architected full-stack AI-powered trading platforms using React.js frontends and Java Spring Boot backends, processing 50M+ daily transactions with 99.99% uptime while integrating Python ML services for predictive analytics. • Built end-to-end machine learning pipelines in Python (TensorFlow, PyTorch, Scikit-learn) for market prediction and risk assessment, deployed via FastAPI microservices, improving trading accuracy by 45% and reducing latency to sub-millisecond levels. • Developed sophisticated React applications with TypeScript, creating real-time dashboards for ML predictions and algorithmic trading signals, seamlessly integrated with Java microservices via REST/GraphQL APIs and WebSocket connections. • Engineered enterprise Java systems using Spring Boot, Hibernate, and Kafka for high-frequency trading, while implementing Python quantitative analysis services, orchestrated through Kubernetes for optimal performance and scalability. • Led hybrid architecture implementation combining Java's reliability with Python's ML capabilities, building React interfaces that visualize complex financial models, resulting in 60% faster decision-making for traders. • Integrated LLMs (GPT-4, Claude) using Python/LangChain for financial document analysis, with Java middleware for data processing and React conversational interfaces, automating 70% of manual research tasks. • Implemented comprehensive testing (JUnit, pytest, Jest, Cypress) achieving 90% coverage across the stack, while mentoring teams on full-stack best practices and AI integration strategies. Tech stack: Java · Spring Boot · Python · React.js · TypeScript · TensorFlow · PyTorch · FastAPI · Kafka · PostgreSQL · Redis · Docker · Kubernetes · AWS · GraphQL · REST · Material-UI · Redux · LangChain · Pandas · NumPy

• Spearheaded the development of a cutting-edge vessel and port management platform, enhancing operational efficiency for marine logistics worldwide. • Led front-end development using React to design user-friendly interfaces for real-time tracking and scheduling of marine assets. • Engineered robust back-end systems using Node.js for seamless data integration and processing capabilities.

Co-founding and leading an open-source AI product for traders. Built backend microservices in NodeJS/Typescript & Go, with API's powered by GraphQL Lead technical vision in delivering enterprise-grade TypeScript/Go applications Frontend with ReactJS, Redux-free & Class-free using latest React Hooks and Apollo GraphQL, Styled-components e.t.c Provide operational coaching and functional mentorship to technical team members DevOps with Kubernetes/Helm 3 on Digital Ocean - I've deployed the cheapest production-ready Kubernetes clusters. Support project estimation, planning, pricing, and proposal delivery CI/CD with Github actions for 3-minutes automatic git push to production deployment Collaborate with designers in creating and implementing project work Staying up-to-date with new/emerging technologies to implement improved practices to overcome technical issues Tech used: Kubernetes / Helm 3, Digital Ocean, Couchbase, Redis, Go, TypeScript, NodeJS, ReactJS, React Native, GraphQL, Github Actions, ML

As Technical Lead the day-to-day operation included, development, coaching, and mentorship of various software development teams leveraging expert knowledge in front & back end, DevOps, and mobile development. Developed and implemented efficient, clean code that satisfied customer requirements. Conducted comprehensive testing and code reviews to ensure that industry coding standards were followed Managed team with regards to task assignments, work arrangements, and other Software Development Department expectations Analyzed call stacks, trace files, debug logs, or performance data to troubleshoot and identify the root cause of bugs, fix defects, and identify areas for improvement Collaborated with other development teams on design and implementation of features spanning multiple products/modules Tech used: Kubernetes / Helm 3, Docker, OpenShift, AWS, Graphana/Prometheus, MongoDB, Redis, TypeScript, NodeJS, ReactJS, Redux, GraphQL

At the center of services that powered customer E-commerce related experiences for all products. worked closely with teams to build and support systems that delivered good user experience, high performance, secure and reliable functionalities. From design, implementation, and deployment Designed, implemented, and iterated on scalable, secure, highly-available, backend services Maintained code quality internally and from outsourced partners Communicated technical risks within and across the group Handled various real-time issues on online services and platform Collected and analyzed metrics from online services Provided input into the product road map, including milestone schedules and deliverables Followed industry trends and maintained a strong cutting edge technology Tech used: Electron(Desktop) TypeScript, NodeJS, ReactJS, React native, Redux, GraphQL

Working on an agriculture startup utilizing transparency of blockchain/hyperledger As a new hire in a startup company, within a period of less than 2 months, I was able to Replace all docker deployments with Kubernetes on GCP Re-deploy all Nodejs web apps as static apps(with NextJS) which reduced 80% of hosting fees Create a mobile version of their main web app with react-native in less than 3 weeks. Tech used: Kubernetes / Helm charts, Docker, GCP, Cloud Run/Build, Firebase, Redis, Postgres, Firestore/Real- time DB, NodeJS, ExpressJS, ReactJS, NextJS, React-Native, Redux/Thunk/Saga, ReactJS Hooks/Context, Apollo GraphQL.

Working on an open-source cloud saas based on Kubernetes I co-founded an open-source tool for deploying web apps with Kubernetes Built backend in NodeJS + Typescript, with API's powered by GraphQL Frontend with ReactJS, Redux-free frontend using latest React Hooks & context. DevOps with Kubernetes - I wrote custom Go lang micro-services for utilizing deployment with Kubernetes, Server costs and deployment dropping to $20 per month - this is the lowest-cost Kubernetes I have ever built running on digital ocean. Tech used: Kubernetes / Helm charts, Docker, Digital Ocean, Firebase, Firestore/Real-time DB, NodeJS, ReactJS, Hooks context, Apollo GraphQL.

Working on CMS's & Car dealership portals, logistics apps e.t.c I handled resources developed by outsourced entities and brought most work back in-house Re-architect and re-design legacy solutions to support increasing growth/scalability Reduced server costs using Kubernetes & Docker Replaced REST APIs with GraphQL e.t.c Tech used: Kubernetes / Helm charts, Docker, AWS, Lambda, CodeBuild, CodePipeline, DynamoDB, Redis, MySQL, MongoDB, NodeJS,ExpressJS, ReactJS, Styled components, NextJS, Gatsby, Redux/Thunk, Apollo GraphQL

IoT devices for providing internet access to rural areas Co-founded and led the development of a decentralized WiFi mesh solution. Configured and built a custom firmware based on OpenWRT for WiFi routers providing free internet. Developed mobile apps for video streaming with WebRTC. Web apps developed in ReactJS+Redux+Apollo connecting to a local GraphQL API. Local deployment on local ubuntu servers Deployed and maintained TURN/STUN servers locally Tech used: IEEE 802.11x, OpenWRT, WebRTC, Redis, MongoDB, NodeJS,ExpressJS, uWebSockets, ReactJS, NextJS, React-Native, Redux, Styled components, Apollo GraphQL