AI/ML Engineer (Generative AI, LLM & Vector Search)

Job Summary

We are seeking a highly skilled AI/ML Engineer with strong expertise in Python, Machine Learning, Generative AI, and Large Language Models (LLMs). The ideal candidate will have hands-on experience designing and deploying scalable, production-grade AI solutions involving model training, prompt engineering, document intelligence, embeddings, vector databases, and semantic search systems.

This role requires deep expertise in enterprise AI application development, fine-tuning LLMs, handling structured and unstructured data, and building production-ready GenAI solutions.

Key Responsibilities

• Design, develop, and deploy scalable AI/ML and Generative AI applications
• Build and optimize LLM-based enterprise solutions
• Perform:
  • Model training
  • Evaluation
  • Fine-tuning
  • Model optimization
• Develop and manage:
  • Tagging and labeling workflows
  • AI training pipelines
  • Data preparation processes
• Implement advanced prompt engineering techniques for LLM-powered applications
• Design document intelligence pipelines including:
  • Document extraction
  • Parsing
  • Chunking
  • Semantic indexing
• Handle both:
  • Structured data
  • Unstructured data
• Build embedding generation and semantic retrieval pipelines
• Integrate and manage:
  • Vector databases
  • MongoDB
  • Vector search frameworks
• Develop scalable, production-ready ML/GenAI systems with high reliability and performance
• Collaborate with engineering, DevOps, product, and business teams for enterprise AI delivery
• Ensure AI solutions align with security, governance, and operational standards

Required Skills & Experience

Core AI/ML Skills

• Expert-level proficiency in Python
• Strong hands-on experience in:
  • Machine Learning
  • Model Training
  • Model Evaluation
  • Fine-tuning
• Experience building and managing:
  • Tagging workflows
  • Data labeling pipelines

Generative AI & LLMs

• Strong understanding of:
  • Generative AI
  • Large Language Models (LLMs)
• Hands-on experience with:
  • Prompt engineering
  • LLM-based applications
  • AI workflow orchestration

Document Processing

• Experience in:
  • Document extraction
  • Parsing
  • Chunking strategies
  • Text preprocessing
• Ability to work with:
  • Structured datasets
  • Unstructured enterprise documents

Embeddings & Vector Search

• Experience with:
  • Embedding generation
  • Semantic search systems
  • Vector similarity search
• Hands-on expertise integrating:
  • Vector databases
  • Retrieval systems

Databases

• Experience with:
  • Vector Databases
  • MongoDB

Production ML Engineering

• Experience building:
  • Scalable ML systems
  • Production-grade GenAI solutions
  • Enterprise AI applications
• Strong understanding of:
  • Performance optimization
  • Reliability
  • Scalability
  • Monitoring

Preferred Qualifications

• Experience with:
  • LangChain
  • LlamaIndex
  • RAG architectures
  • Open-source LLM frameworks
• Familiarity with:
  • AWS / Azure / GCP AI services
  • MLOps and CI/CD pipelines
  • GPU-based model training
• Experience deploying AI solutions in enterprise environments

Key Competencies

• Python Development
• Machine Learning Engineering
• Generative AI & LLMs
• Prompt Engineering
• Document Intelligence
• Embeddings & Vector Search
• Vector Database Integration
• Production ML Engineering
• Scalable AI Architecture