Machine Learning Engineer

• Designs and develops scalable machine learning models and AI-driven

  solutions to address complex business challenges and enhance decision-

  making processes

  KEY RESPONSIBILITIES

  • Work with large and complex data sets to solve challenging business

  problems

  • Efficient training and deployment of standard ML, NN, and Agentic models.

  • Develop, train, and optimize machine learning models using state-of-the-art

  algorithms and frameworks

  • Build production grade end-to-end ML pipelines, including data ingestion,

  transformation, model training, validation, and deployment

  • Automate workflows for model training, testing, and deployment using

  CI/CD pipelines and MLOps tools

  • Collaborate with cross-functional teams to integrate models into applications

  and deliver end-to-end solutions

  • Finetune SLMs/LLMs and build complex AI architectures

Desired Candidate Profile

• (3-7) years of experience in building production grade, scalable AI systems.

  • Expert in supervised/unsupervised learning, deep learning, NLP, computer

  vision, or generative AI (e.g., LLMs).

  • Strong ML system architecture skills

  • Understanding of model serving, API development (FastAPI, Flask), and

  optimizing model performance for real-time or batch inference.

  • General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like

  MLflow/Kubeflow for model lifecycle management (MLOps)

  • Comfortable with deploying models on AWS or Azure

  • Minimum Educational qualifications: Bachelor’s degree in Computer Science,

  Engineering, or related field required

  Classified: Internal\ FAB

  Internal

  • Preferred Education qualifications: Master or PhD in Computer Science or a

  related field.

  Work Experience

  7-10Years