We're seeking a talented Python Backend Engineer with expertise in FastAPI.
The backend engineer is responsible for building/managing APIs for AI applications, introducing AI-based innovations, optimizing existing setups and resulting in seamless integrations.
Responsibilities:
- Build high-performance REST APIs & WebSockets to power our frontend experiences
- Design, develop, and maintain scalable and efficient backend services for ML model deployment and inference using FastAPI for our AI-driven product.
- Coordinating with development teams to determine application requirements and integration points.
- Understanding of fundamental design principles behind a scalable application and writing scalable code
- Implement security best practices to safeguard sensitive data and ensure compliance with privacy regulations
- Own and manage all phases of the software development lifecycle planning, design, implementation, deployment, and support.
- Build reusable, high-quality code and libraries for future use which are performant and can be used across multiple projects.
- Work closely with data engineers and data scientists to integrate ML models into the production environment
Qualifications:
- Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent work experience).
- At least 3.5+ years of relevant experience as a Python Backend Engineer
- A strong background in designing and building RESTful with Python FastAPI and WebSocket APIs, including familiarity with API design best practices
- Good experience in developing web technology solutions including HTTP/HTTPS protocols and WebSocket communication
- Experience in Quick API for API development, SQL/NoSQL databases designing and linux o.s.
- Good exposure with ML algorithms, Python, NLP, prior experience with backend design and web sockets
- Knowledge of basic algorithms, object-oriented and functional design principles, and best-practice pattern
- Experience with Cloud based AI/ML services (AWS Preferred)
- Practical experience in applying AI/ML driven technology solutions
- Understanding of ML/AI Pipeline & Development life cycle & tools, MLOps experience
- Good knowledge of software engineering practices like version control (GIT) and DevOps (Azure DevOps preferred)