Advanced Machine Learning Specialist

19 hours ago

Mumbai, Maharashtra, India beBeeKnowledge Full time ₹ 1,50,00,000 - ₹ 2,00,00,000
Machine Learning Engineer - AI Development Team

 

Role Overview

As a senior member of our AI development team, you will lead the design and implementation of machine learning pipelines that power our product.

Our ideal candidate has extensive experience in developing and deploying production-ready machine learning models using Python, PyTorch, and TensorFlow. They must have strong knowledge of natural language processing (NLP) concepts, including deep learning architectures and vector databases.

The selected candidate will work closely with our engineering team to architect and scale our ML pipelines, implementing multi-LLM and multi-agent orchestration. They will also be responsible for designing and optimizing RAG pipelines, building connectors to integrate with external systems, and adapting and fine-tuning models for various workflows.

Key Responsibilities:

  • Design and implement machine learning pipelines that meet business requirements.
  • Develop and deploy production-ready machine learning models using Python, PyTorch, and TensorFlow.
  • Work with the engineering team to architect and scale ML pipelines.
  • Implement multi-LLM and multi-agent orchestration using tools such as LangGraph or equivalents.
  • Design and optimize RAG pipelines for hierarchical chunking, embeddings, hybrid search, and re-ranking.
  • Build and maintain connectors to integrate with external systems.
  • Adapt and fine-tune models for Finance, Legal, and Tax workflows.
  • Deploy and monitor models in production using APIs, tracing, metrics, and balancing cost with performance.

Requirements:

  • 4-5 years of experience as a Machine Learning Engineer/Applied Scientist working in production environments.
  • Strong expertise in Python (FastAPI/Flask), PyTorch/TensorFlow, and data pipeline management.
  • Deep understanding of NLP concepts, including LLMs, RAG systems, embeddings, and vector DBs.
  • Experience working with multiple LLM providers and balancing cost, latency, and quality.
  • Comfortable with Docker, Kubernetes, CI/CD, and deploying to cloud platforms like AWS/GCP.

What We Offer:

  • End-to-end ownership and visibility, with your code running in production.
  • A front-row seat to shape how agentic AI gets applied to real-world problems.
  • Opportunities to build from scratch the AI backbone of a product targeting significant revenue opportunities.

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