Senior ML Engineer with Python (IR-536)
Tasks
- Build LLM observability
- Build backend APIs
- Deploy and operationalize ML models
- Design multi-tenant architectures
- Develop machine learning and LLM systems
- Develop prompt management systems
- Document API changes with OpenAPI
- Implement MLOps pipelines
- Implement asynchronous task workflows
- Implement dependency injection and layered architecture
- Integrate LLM providers
- Optimize LLM cost and performance
- Orchestrate model pipelines
- Research and prototype new architectures
- Scale ML algorithms for large datasets
- Troubleshoot using logging and distributed tracing
- Write unit tests and higher level tests
Perks/Benefits
- Career growth path
- Extra absence days
- Flexible hours
- Team events
- Training budget
- Work from anywhere
- Workshops
Skills/Tech-stack
A/B | A/B Testing | Async/Await | Asyncio | Azure Blob | Azure Blob Storage | Azure Key Vault | Azure OpenAI | B testing | Batch inference | Blob Storage | Celery | Chroma | Computer Vision | Dependency Injection | Distributed tracing | Docker | FastAPI | Feature Engineering | GPT-4 | GPT-4 Vision | Hugging Face | Hybrid search | Key Vault | Kubernetes | Kubernetes deployment | Langchain | Langgraph | Llamaindex | MLOps | MLflow | Microservices | Model Serving | Model versioning | NLP | OCR | OpenAI API | OpenAPI | Pinecone | PostgreSQL | Pydantic | Python | Quota Management | RAG | Rate Limiting | Real Time | Real-time Inference | SOLID | SQL | SQLAlchemy | Structured Logging | Swagger | Transformer Models | Type Hints | Vector Databases | Weaviate
Education
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