Machine Learning Engineer (fullstack)

Build AI-powered user experiences by developing front-end interfaces and backend services that integrate LLMs, chatbots, and intelligent automation workflows.

Responsibilities

• Design and develop modern front-end interfaces (React, Angular, Streamlit) tailored for AI-driven workflows, chat interfaces, dashboards, and model output visualization.
• Build backend APIs and microservices (Node.js, Python Flask/FastAPI) to serve LLMs, RAG pipelines, vector DBs, and user-facing applications securely and efficiently.
• Integrate AI/ML models through REST, WebSockets, or gRPC, ensuring low latency, scalability, and reliable inference pipelines.
• Implement real-time AI features such as chatbots, conversational UI, document processing apps, recommendation engines, and intelligent agents.
• Automate workflows using UiPath or similar orchestration tools when AI-driven tasks require robotic or enterprise automation.
• Develop and maintain reusable UI components for prompt interfaces, model monitoring, and human-in-the-loop review flows.
• Write unit, integration, and end-to-end tests to ensure stability, correctness, and reliability across AI application layers.
• Optimize performance, manage deployments, and scale applications using CI/CD pipelines, Docker, Kubernetes, and cloud-native infrastructure.
• Collaborate with AI/ML engineers to connect UI/UX requirements with underlying model behavior, context pipelines, and evaluation workflows.