AI / ML Engineer

Role overview

Responsibilities

• check_circle Design, develop, train, and deploy machine learning and deep learning models for enterprise applications.
• check_circle Build and optimize end-to-end ML pipelines for data ingestion, model training, evaluation, and deployment.
• check_circle Develop Generative AI and LLM-powered applications using modern AI frameworks.
• check_circle Collaborate with data engineers, software developers, and business stakeholders to deliver AI-driven solutions.
• check_circle Deploy and monitor ML models on cloud platforms while ensuring scalability, reliability, and security.
• check_circle Optimize model performance through feature engineering, hyperparameter tuning, and continuous evaluation.
• check_circle Implement MLOps best practices including model versioning, monitoring, and CI/CD automation.
• check_circle Stay current with advancements in AI, machine learning, and cloud AI services.

Basic qualifications

• Bachelor's degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related field.
• <strong>3–11 years</strong> of professional experience in AI, Machine Learning, or Data Science.
• Strong analytical, mathematical, and problem-solving skills.
• Experience working in Agile development environments.
• Excellent communication and collaboration skills.

Preferred qualifications

• Experience with Large Language Models (LLMs) and Generative AI applications.
• Knowledge of Retrieval-Augmented Generation (RAG), vector databases, and AI agents.
• Experience with distributed model training and cloud-native AI architectures.
• Cloud certifications in AWS, Azure, or Google Cloud are a plus.