Senior ML Engineer with Python (IR-536)
Core
Build, refine, and operationalize scalable ML Engineering platforms and components, specifically focusing on LLMs, Generative AI, and backend systems for an AI-powered decision-making platform.
Role type
Senior Machine Learning Engineer (LLM/GenAI)
Builds
Scalable backend systems, APIs, microservices, and production ML/Deep Learning models (LLMs, GenAI)
Domain
Enterprise AI, Generative AI, Large Language Models (LLMs), Cloud Infrastructure
Deliverable
production ML models | product features | infrastructure
Required skills
Python (async/await, type hints, Pydantic, SOLID), Machine Learning, Production LLM systems, FastAPI, Vector databases (Pinecone, Weaviate, Chroma), RAG architectures, LangChain, LangGraph, Hugging Face, MLOps (MLflow, model versioning, A/B testing), NLP, Computer Vision, SQL, Feature pipelines, Model serving
Preferred skills
Azure (Azure OpenAI, Blob Storage, Key Vault), LlamaIndex, Langfuse, Celery, DevOps (Docker, Kubernetes, CI/CD), Big Data systems, Document processing (OCR, PDF extraction), Prompt management, Cost optimization for LLMs
Technologies
Python, FastAPI, SQLAlchemy, Pinecone, Weaviate, Chroma, LangChain, LangGraph, Hugging Face, MLflow, Azure OpenAI, Celery, Docker, Kubernetes, Azure DevOps, GitHub Actions, Langfuse, OpenAPI/Swagger
Responsibilities
Develop and implement scalable backend systems and microservices using FastAPI; Deploy and operationalize ML and Deep Learning models with a focus on LLMs and Generative AI; Implement MLOps including model KPI measurement, tracking, drift detection, and feedback loops; Build and orchestrate model pipelines including feature engineering, inferencing, and continuous model training; Integrate Azure OpenAI and other LLM providers with proper retry logic and error handling; Build multi-tenant architectures with client data isolation; Implement cost optimization strategies for LLM usage; Write production-ready code that is testable, maintainable, and accounts for edge cases and errors; Troubleshoot backend application code using structured logging and distributed tracing; Research and evaluate emerging architecture patterns and technologies through rapid learning, proofs-of-concept, and prototypes.
Seniority
Senior, hands-on IC