AI Machine Learning Engineer

AI Engineer / Machine Learning Engineer

Role Overview

We are seeking a highly skilled AI Engineer / Machine Learning Engineer with deep expertise in building, optimizing, and deploying advanced AI systems. The ideal candidate has strong experience with LLM-based architectures, vector databases, distributed AI agents, and end-to-end machine learning lifecycle management.

Key Responsibilities

• Design, develop, and deploy ML/DL models for production environments.
  

• Build and optimize LLM-based systems including RAG pipelines, embeddings, and retrieval workflows.
  

• Architect, implement, and maintain vector database solutions (Weaviate, Pinecone, Chroma, Qdrant).
  

• Develop backend systems using FastAPI and microservice patterns.
  

• Implement distributed AI agent systems and multi-agent orchestration.
  

• Integrate ML models into full-stack applications (Python backend, Next.js frontend).
  

• Oversee MLOps processes including model training, versioning, deployment, monitoring, and CI/CD integration.
  

• Collaborate with product, data, and engineering teams to deliver scalable AI solutions.
  

Required Skills & Qualifications

• ML / Deep Learning: Advanced expertise in training and deploying models.
  

• LLM, RAG & Embeddings: Advanced proficiency with modern LLM frameworks and retrieval-augmented generation.
  

• Vector Databases: Expert-level experience with Weaviate, Pinecone, Chroma, or Qdrant.
  

• Backend Architecture: High-level proficiency with FastAPI, microservices, and modern API design.
  

• Python & PyTorch: Strong development and deployment experience.
  

• Next.js: Practical understanding of client/server communication and integration with AI backends.
  

• Distributed AI Agents: Deep understanding of agent-based AI systems.
  

• MLOps: Experience with model lifecycle management is a strong advantage.