AI Engineer

Experience:

Role Overview

AI Engineer

Key Responsibilities

• Design, develop, and deploy AI/ML models for prediction, classification, scoring, and automation.
  
• Build and evaluate models using

  TensorFlow, PyTorch, Scikit-learn

  , and

  Hugging Face

  .
• Implement ML pipelines including data preprocessing, feature engineering, training, validation, and model serving.
  
• Develop deep learning solutions for

  NLP, document intelligence, computer vision, and voice AI

  .
• Support voice-based projects (Speech-to-Text, Text-to-Speech, conversational AI).
  
• Integrate LLM and AGI-driven solutions using

  OpenAI APIs, LangChain

  , and similar frameworks.
• Work closely with backend and data teams to integrate models into production environments.
  
• Conduct model monitoring, drift detection, evaluation, and retraining.
  
• Stay current with new AI frameworks, cloud ML tools, and best practices.
  
• Participate in research initiatives and proof-of-concept development.
  

Required Skills & Expertise

• Strong programming skills in

  Python

  , with good grasp of algorithms and data structures.
• Hands-on experience with

  TensorFlow, PyTorch, Scikit-learn, Hugging Face

  , LLMs, and OpenAI APIs.
• Experience in machine learning (supervised/unsupervised), NLP, computer vision, and predictive analytics.
  
• Experience deploying models on

  AWS, Azure, or GCP

  .
• Knowledge of

  MLOps

  , including model versioning, Docker, CI/CD, and monitoring.
• Familiarity with SQL/NoSQL databases, ETL workflows, and data pipelines.
  
• Understanding of voice AI technologies and LLM-based architectures.
  
• Knowledge of AGI concepts is an added advantage.
  

Preferred Domain Experience

• AI use cases in:
  
• Core banking
  
• Credit risk modeling
  
• Fraud/anomaly detection
  
• Customer analytics
  
• Chatbots and voice banking
  
• Experience working with banks, NBFCs, or fintech platforms preferred.
  

Soft Skills

• Strong analytical and problem-solving abilities.
  
• Clear communication skills for cross-functional collaboration.
  
• Research-oriented mindset with adaptability to emerging technologies.
  
• Ability to independently own end-to-end tasks, while also working well within a team.
  
• Commitment to documentation, learning, and mentoring juniors when required.
  

Education

• Bachelors or Master’s degree in Computer Science, AI, Data Science, Machine Learning, or related field.
  
• Relevant certifications in AI/ML, deep learning, or cloud ML are preferred.
  

Compensation & Benefits

• Competitive salary based on experience and skills.
  
• Opportunity to work on cutting-edge AI, LLM, and fintech solutions.
  
• Collaborative and growth-focused work environment.

  Role & responsibilities

Preferred candidate profile