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Senior Python Backend Developer & ML Engineer

Intellectsoft

Senior 🇬🇧 English
Python FastAPI SQLAlchemy async/await Pydantic SOLID principles Pinecone Weaviate Chroma RAG LangChain LangGraph MLflow Langfuse Hugging Face GPT-4 Vision OCR SQL Docker Azure DevOps GitHub Actions Kubernetes Azure OpenAI Azure Key Vault

Descripcion del puesto

About the role

We are looking for a Senior Python Backend Developer and ML Engineer to join our AI‑powered platform team. You will help build scalable backend services and advanced machine‑learning pipelines that enable businesses across industries, including healthcare, to make data‑driven decisions.

Key responsibilities

  • Design, develop, and maintain high‑performance APIs using FastAPI, async patterns, and SQLAlchemy.
  • Build and operate ML engineering platforms, including feature pipelines, real‑time and batch inference, and model serving.
  • Implement Retrieval‑Augmented Generation (RAG) architectures, integrating vector databases and LangChain/LangGraph workflows.
  • Collaborate with data scientists to version models, run A/B tests, and monitor production performance.
  • Contribute to code quality, testing strategies, and documentation for non‑deterministic LLM outputs.

Required profile

  • Bachelor's or Master's degree in Computer Science or a related field.
  • 7+ years of professional Python development experience.
  • 2+ years of hands‑on experience with machine learning and production LLM systems.
  • Strong problem‑solving abilities and comfort working in a fast‑paced, team‑oriented environment.

Required skills

  • Python (async/await, type hints, Pydantic, SOLID principles)
  • FastAPI, SQLAlchemy, rate limiting, dependency injection
  • Vector databases: Pinecone, Weaviate, Chroma
  • RAG architectures, LangChain, LangGraph
  • MLOps tools: MLflow, model versioning, A/B testing (Langfuse optional)
  • NLP & computer‑vision frameworks: Hugging Face, GPT‑4 Vision, OCR, document understanding
  • Database technologies: SQL
  • Containerization and CI/CD: Docker, Azure DevOps pipelines, GitHub Actions, Kubernetes (optional)
  • Cloud platforms: Azure (OpenAI, Blob Storage, Key Vault, Container Registry) – preferred

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Publicado hace 2 meses

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