Technologies: Rust, Large Language Models (LLMs), Model Training, PyTorch, TensorFlow, Distributed Systems, Docker, Kubernetes- Developed and optimized a high-performance Generative AI application using **Rust** for its backend, focusing on efficient, low-latency processing of large-scale AI models.- Implemented and fine-tuned **Large Language Models (LLMs)** for various generative tasks, including text generation, summarization, and question-answering.- Led model training pipelines using frameworks such as **PyTorch** and **TensorFlow**, enabling efficient training and fine-tuning of LLMs on large datasets.- Architected a scalable and distributed system to handle high-volume requests, utilizing **Docker** for containerization and **Kubernetes** for orchestration and scaling across cloud environments.- Worked on optimizing inference times and memory usage to ensure smooth deployment and real-time interaction with trained models in production.- Collaborated with data scientists and machine learning engineers to implement advanced algorithms and ensure robust performance across different generative AI tasks.- Integrated feedback loops and continuous learning mechanisms to enhance model accuracy and performance over time.

Technologies: C#, Go, Blockchain, Smart Contracts, Distributed Systems, Docker, Kubernetes, PostgreSQL, Redis, CI/CD- Led the server-side development of a decentralized application (DApp) for cryptocurrency transactions, focusing on scalability, security, and distributed ledger integration.- Architected and implemented microservices using C# and Go, enabling high-performance, concurrent processing of blockchain-based transactions.- Integrated blockchain protocols and smart contracts, ensuring secure, trustless transactions, and seamless interaction with cryptocurrency wallets and nodes.- Managed the application’s infrastructure using Docker for containerization and Kubernetes for orchestration, facilitating easy deployment and scaling.- Designed and maintained a robust database layer using PostgreSQL for long-term data storage and Redis for real-time data caching, optimizing performance for transaction-heavy operations.- Implemented CI/CD pipelines to automate testing, integration, and deployment, ensuring rapid development cycles and continuous delivery of features and updates.- Collaborated closely with blockchain experts, front-end developers, and DevOps teams to ensure smooth integration with the blockchain network and secure handling of crypto assets.- Oversaw code reviews, team mentorship, and best practice implementation in software design, development, and testing.

Technologies: Python, gRPC, Docker, Kubernetes, PostgreSQL, Redis, Unit Testing, Integration Testing, Performance Testing, CI/CD (Jenkins, GitLab), Microservices Architecture- Developed the server-side architecture for a financial blotter application dedicated to managing and processing crypto assets trade data.- Implemented gRPC APIs to handle and respond to custom queries, facilitating fast and secure communication across services.- Built comprehensive unit tests to ensure reliability and correctness, alongside integration tests to validate the seamless interaction between components.- Performed extensive performance testing to optimize system response times and throughput, ensuring scalability for high-volume crypto trades.- Maintained application scalability and high availability, addressing the unique challenges of crypto asset data processing.- Collaborated with cross-functional teams to ensure smooth integration with other crypto asset systems and workflows.