Full Stack Engineer (AI / Machine Learning) [33319]

We're looking for a Full Stack Engineer with experience building AI or Machine Learning-powered applications. You'll work across the entire technology stack—from intuitive frontend interfaces to scalable backend services—while integrating and deploying ML models and AI capabilities into production.This role is ideal for engineers with 1–2 years of professional experience who have demonstrated strong technical ability and a passion for building AI-driven products in a fast-paced startup environment.ResponsibilitiesDesign, build, and maintain full stack web applications using modern frontend and backend technologies.Develop scalable backend APIs and services that support AI/ML features.Integrate machine learning models, LLMs, or AI APIs into customer-facing applications.Collaborate with product, design, and engineering teams to deliver new features quickly.Build responsive, high-performance user interfaces with modern JavaScript frameworks.Optimize application performance, scalability, and reliability.Write clean, maintainable, and well-tested code.Participate in code reviews and contribute to engineering best practices.QualificationsBachelor's or Master's degree in Computer Science or a related field.1–2 years of professional experience as a Full Stack Software Engineer.Strong experience with JavaScript/TypeScript.Experience with frontend frameworks such as React, Next.js, or similar.Experience building backend services using Node.js, Python, Go, or Java.Experience working with relational and/or NoSQL databases.Familiarity with REST APIs, GraphQL, and cloud platforms (AWS, GCP, or Azure).Experience integrating AI/ML solutions, including LLM APIs or machine learning models.Strong understanding of software engineering fundamentals and system design.Preferred QualificationsExperience building AI-native or ML-powered products.Familiarity with OpenAI, Anthropic, Google Gemini, or similar AI platforms.Experience with PyTorch, TensorFlow, or other ML frameworks.Knowledge of vector databases, RAG pipelines, embeddings, or MLOps.Experience with Docker, Kubernetes, CI/CD, and cloud-native architectures.Previous startup experience or experience working in high-growth environments.