Backend Machine Learning Engineer

1 day ago


Jodhpur, Rajasthan, India beBeeBackend Full time US$ 1,00,000 - US$ 1,40,000
Job Opportunity

We seek an expert in machine learning engineering with strong background in backend development and hands-on experience building scalable AI systems using generative technologies.

This role combines AI and payment technology to develop innovative genAI-driven applications, design intelligent agents, and contribute to the development of robust Python-based backend systems.

Key Responsibilities:
  • Design, implement, and maintain high-performance Python-based backend systems with focus on scalability, security, and reliability.
  • Integrate and work with AI agent frameworks, agentic development patterns, and related technologies.
  • Develop and deploy RAG pipelines and intelligent APIs powered by generative AI.
  • Work with relational databases such as MySQL and PostgreSQL for structured data management.
  • Utilize Docker for containerization and deploy services in microservices architecture.
  • Collaborate with cross-functional teams to drive innovation and delivery of AI-first features.
  • Apply prompt engineering techniques to fine-tune LLM interactions and outputs.
  • Stay current with emerging trends in generative AI and continuously explore ways to apply them within our systems.
Requirements:
  • 4 to 8 years of professional experience in backend development using Python.
  • Strong experience with object-oriented programming and backend software engineering.
  • Experience working with AI agent frameworks (e.g., LangChain, AutoGPT).
  • Solid understanding of RESTful API design and implementation.
  • Hands-on experience with relational databases (MySQL, PostgreSQL).
  • Proficiency with version control tools, especially Git.
  • Familiarity with Docker for containerization and environment replication.
  • Experience working with microservices and distributed systems.
  • Working knowledge of Vibe or similar AI coding tools.
  • Strong understanding and experience with generative AI technologies (e.g., LLMs, RAG, prompt engineering).
  • Demonstrated ability to creatively apply genAI in solving real-world problems.


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