AI Engineer

Key Responsibilities

• Design, develop, and deploy AI/ML solutions to solve business challenges and create value from data.
• Build, train, evaluate, and optimize machine learning and generative AI models.
• Develop scalable AI pipelines and integrate AI services into production environments.
• Collaborate with Data Scientists, Data Engineers, Product Managers, and business stakeholders to deliver end-to-end AI solutions.
• Monitor model performance, ensure reliability, and continuously improve AI systems.
• Stay up to date with advancements in AI, machine learning, and generative AI technologies.

Required Qualifications

• 5–6 years of experience in AI Engineering, Machine Learning Engineering, or a related role.
• Strong proficiency in Python and machine learning frameworks such as Tensor

  Flow, Py

  Torch, or Scikit-learn.
• Experience deploying AI/ML models in production environments.
• Solid understanding of machine learning algorithms, deep learning, NLP, and MLOps practices.
• Experience with cloud platforms (AWS, Azure, or GCP) and AI services.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.

Nice to Have

• Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and AI agents.
• Knowledge of vector databases and model serving frameworks.
• Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker.
• Exposure to CI/CD pipelines and Infrastructure as Code (IaC).

Soft Skills

• Strong analytical and problem-solving skills.
• Excellent communication and stakeholder management abilities.
• Ability to work independently in a fast-paced environment.
• Curiosity and passion for emerging AI technologies and innovation.