I'm a highly motivated Senior Machine Learning Engineer specializing in designing, building, and maintaining scalable infrastructure for machine learning model evaluation and research inference. My core focus is on driving ML initiatives from Proof-of-Concept through to large-scale production systems capable of supporting thousands of users, delivering solutions with exceptional performance, reliability, and scalability.

• ✨ Lead ML Initiatives: Experience in leading a team of 3 engineers to deliver production ML features with high precision and performance.
• 🏗️ Build Scalable ML Systems: Design and implement robust ML pipelines using technologies like vector databases, VLMs, and LLMs for scalable systems.
• 🚀 Optimize & Deploy Models: Expertise in optimizing and deploying models to cloud (GPUs) and edge devices (Apple silicon) for inference.
• 🛡️ Develop Robust Infrastructure: Implement robust CI/CD pipelines, unit tests, and system monitoring. Design scalable DB schemas, build high-performant APIs, and develop A/B test cron-based production systems.
• 💡 Solve Complex Problems: Applied ML to diverse domains including text search, video search, medical image analysis, face recognition, and data digitization.

• 💻 Programming Languages: Python, JavaScript, TypeScript, Bash, Go, C++, HTML/CSS, SQL.
• 📚 Libraries & Frameworks: TensorFlow, PyTorch, Scikit-Learn, JAX, HuggingFace, OpenCV, PySpark, Pandas, Flask, FastAPI, NTLK.
• 🛠️ Tools & Platforms: Docker, Kubernetes, AWS, GCP, Azure, Git, Linux, NodeJS, DynamoDB, PostgreSQL, MySQL, Elasticsearch, Qdrant, RabbitMQ, GraphQL, GitHub Actions, GitLab CI, Jenkins, Prometheus, Grafana, Nvidia Trition, Redis.
• 🧠 ML Concepts: LLMs, VLMs, Vector Databases, Data Validation, Preprocessing, Model Optimization, Cloud Deployment, Edge Deployment (MLX), CI/CD, Monitoring, A/B Testing, API Development, Database Design, Frontend Contribution.