Machine Learning Engineer

We're looking for a seasoned Machine Learning Engineer with a strong background in event-driven architecture, real-time systems, and AI/LLM integration. You'll be responsible for architecting and implementing high-performance, distributed systems with dynamic functionality, real-time processing, and seamless AI model interaction. This role is perfect for someone passionate about deep Python internals and building intelligent infrastructure at scale.
Responsibilities:
Design and develop scalable, distributed systems using Python.
Build and maintain LLM/AI integration pipelines (OpenAI, Azure OpenAI, open-source models).
Develop real-time communication systems (text/voice over WebSockets).
Create dynamic function registration and runtime execution frameworks.
Implement robust error handling, monitoring, and logging systems.
Write clean, modular, and well-documented code following best practices.
Collaborate with cross-functional teams on system architecture and performance tuning.
Requirements:
5+ years of professional Python development experience.
Strong problem-solving and debugging skills.
Excellent written and verbal communication.
Self-starter with close attention to detail.
Comfortable reviewing code, writing documentation, and mentoring peers.
Ability to understand and manage complex system interactions.
Expertise in:
Advanced Python: decorators, metaclasses, async/await, etc.
Asynchronous programming with asyncio.
Event-driven architecture and WebSocket communication.
Dynamic function registration and runtime execution.
Dependency injection and context management patterns.
Type hints, Pydantic, and runtime type enforcement.
Deep understanding of:
OpenAI / Azure OpenAI API integration.
Real-time communication protocols.
API design (REST, GraphQL optional).
Error handling in distributed systems.
Logging and monitoring (e. g., Sentry, custom metrics).
Testing strategies (unit, integration, mocking async flows).
Nice to Have:
Experience with:
Deploying open-source LLMs on Azure (e. g., HuggingFace Transformers, Llama.cpp, etc. ).
FastAPI, GraphQL, or similar modern Python frameworks.
Docker, Kubernetes, and containerized deployments.
CI/CD pipelines and release automation.
Sentry, Prometheus, or other observability platforms.

Experience
3-6 yrs