What You'll Do

Design and implement end-to-end AI features that integrate machine learning models, algorithms, and inference services into production applications while collaborating with technology stakeholders. Develop APIs and backend services using Node.js and/or Python (FastAPI/Flask) to operationalize trained models. Translate experimental ML outputs into stable, user-facing functionality while adhering to technical stakeholder requirements. Implement deployment patterns for ML models using containerization and CI/CD workflows. Integrate services built with TensorFlow, PyTorch, or scikit-learn models into scalable application layers. Develop and optimize AI-driven workflows, including retrieval‑augmented generation (RAG), vector search, and agentic tool execution frameworks. Build responsive interfaces using React/Next.js and TypeScript to support AI features. Design UI states that communicate model progress, confidence indicators, and safe failure modes. Independently o...