Full-Stack AI Engineer

Full-Stack AI Engineer (React / Python)
Location: Cupertino, CA (5x/ week onsite)

Job Summary

We are seeking a versatile Full-Stack AI Engineer to join our product team. You will be responsible for building end-to-end applications that leverage modern web technologies and state-of-the-art AI/ML models. The ideal candidate thrives on the intersection of intuitive UI/UX design and the underlying complexity of machine learning pipelines.

Key Responsibilities
• Frontend Development: Design and implement highly responsive, interactive user interfaces using React (18+) and TypeScript.
• I Integration: Architect and deploy AI-driven features such as LLM-powered chatbots, RAG (Retrieval-Augmented Generation) pipelines, and recommendation engines.
• Backend & APIs: Build scalable REST or GraphQL APIs and serverless backend services to handle complex AI inference tasks.
• Model Implementation: Integrate models from platforms like OpenAI, Hugging Face, or Anthropic using frameworks like LangChain.
• Database Management: Design and optimize schemas for both traditional databases (PostgreSQL, MongoDB) and Vector Databases (Pinecone, Weaviate).
• MLOps: Collaborate on model deployment, monitoring, and fine-tuning to ensure production-grade performance and reliability.

Required Skills & Qualifications
• Frontend: Proficiency in React.js, and modern CSS frameworks like Tailwind CSS.
• Backend: Strong experience with Node.js or Python (Django/FastAPI).
• I/ML: Hands-on experience with Prompt Engineering, LLM APIs, and fine-tuning machine learning models.
• ML Frameworks: Familiarity with PyTorch or TensorFlow.
• Cloud & DevOps: Experience with AWS (SageMaker, Lambda) or GCP for deploying AI solutions.
• Experience: Min 5+ years in full-stack development with a proven portfolio of AI-integrated projects.

Preferred Qualifications
• Contributions to open-source AI projects.
• Certifications in AI/ML from Coursera (Andrew Ng), Google, or AWS.
• Knowledge of MLOps best practices (tracking, versioning, and monitoring models).