Full-Stack AI/ML Application Engineer
Role Overview
Design and build end-to-end applications integrating AI/ML and LLM capabilities into production-grade products.
Own reliable, scalable full-stack AI features from model integration and deployment to APIs, data pipelines, and optimization.
Deliver measurable improvements in accuracy, latency, and system robustness.
Key Skills for This Role
Full Job Posting
Role overview
Design and build end-to-end applications integrating AI/ML and LLM capabilities into production-grade products.
Own reliable, scalable full-stack AI features from model integration and deployment to APIs, data pipelines, and optimization.
Deliver measurable improvements in accuracy, latency, and system robustness.
Responsibilities
- Develop full-stack applications, including Python backend services and TypeScript/JavaScript frontend and services.
- Build and own scalable REST or GraphQL APIs and data pipelines.
- Integrate machine-learning models and LLM capabilities, including prompt engineering.
- Deploy models using tools such as FastAPI and Docker.
- Design database access using PostgreSQL or MongoDB and engineer cloud platforms.
- Implement CI/CD and automated testing, and use Git for version control.
- Optimize performance and strengthen security.
Required qualifications
- Proficiency in Python and TypeScript/JavaScript.
- Experience building REST and/or GraphQL APIs.
- Hands-on machine-learning model integration using PyTorch and/or TensorFlow.
- Experience with LLM integration and prompt engineering.
- Model deployment experience, such as with FastAPI or Docker.
- Experience with PostgreSQL and/or MongoDB, and with AWS, GCP, or Azure.
- Strong CI/CD fundamentals, test automation, and Git version-control skills.
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