AL/ML Engineer

DigiWagon builds AI-powered, data-driven
products that help enterprises improve agility, automate intelligence, and
deliver meaningful customer experiences. By combining artificial intelligence,
automation, and human-centered design, we enable organizations to scale
innovation and achieve sustainable digital growth.

We are looking for an AI/ML Engineer with hands-on experience in building and deploying LLM-powered applications,
RAG pipelines, and AI-driven systems. You will work on real-world AI/ML
products involving NLP, embeddings, vector search, and agent-based workflows,
collaborating closely with backend, data, and product teams to deliver
production-ready AI solutions.

This role is ideal for engineers who enjoy applied
AI, system design, and transforming ML concepts into scalable, usable
applications.

• Strong proficiency in Python for AI/ML development
  
• Experience working on AI/ML-based
  products, particularly LLM-powered applications
  
• Hands-on experience with LangChain,
  LangGraph, and prompt engineering techniques
  
• Strong understanding of prompt design, prompt optimization, and
  RAG pipelines
  
• Experience designing AI/ML application architectures involving: LLMs,
  Embeddings, Vector databases
  
• Embedding search frameworks (FAISS or similar)
  
• Solid knowledge and hands-on experience in Natural Language
  Processing (NLP)
  
• Understanding of different ML
  model types and their use cases, including: Linear and logistic regression,
  Neural networks, Traditional ML vs deep learning approaches
  
• Experience with AI/ML libraries and tools such as: PyTorch,
  TensorFlow, scikit-learn, Hugging Face
  
• Experience or exposure to fine-tuning pre-trained models (LLMs or traditional ML models) for domain-specific use cases
  
• Knowledge and exposure to Agentic
  AI concepts, including multi-step reasoning and tool-based agents
  
• Understanding of MLOps
  practices, including model versioning, experimentation, deployment, and
  monitoring
  
• Experience validating and
  testing AI/ML pipelines, models, and outputs
  
• Ability to integrate existing
  ML models into production pipelines and applications
  
• Strong analytical thinking,
  problem-solving skills, and ability to collaborate with cross-functional teams
  
• Good communication skills and a
  product-oriented mindset
  

Responsibilities:

• Design
  and develop AI/ML-powered applications using LLMs, embeddings, and
  vector search
  
• Build,
  optimize, and maintain RAG pipelines for retrieval-based AI systems
  
• Implement effective prompt engineering
  and prompt optimization strategies
  
• Develop
  and integrate NLP solutions for real-world use cases
  
• Fine-tune pre-trained models when required to improve domain relevance, accuracy,
  or performance
  
• Design and integrate Agentic AI workflows, including
  Tool-based agents, multi-step reasoning pipelines, Orchestration using
  frameworks like LangChain and LangGraph
  
• Select,
  evaluate, and apply appropriate ML models based on product requirements
  
• Integrate
  custom and pre-trained ML models into scalable AI pipelines
  
• Collaborate
  with backend and platform teams to deploy AI services into production
  
• Apply MLOps best practices for model lifecycle management and monitoring
  
• Test,
  evaluate, and validate AI/ML systems for quality, reliability, and performance
  
• Troubleshoot AI/ML pipeline issues and
  perform Root Cause Analysis (RCA)
  
• Continuously
  explore and adopt new AI/ML techniques to enhance product capabilities