AI Engineer

Highly skilled Machine Learning Engineer to design, build, deploy, and scale machine learning models that power data-driven products and intelligent systems.

Requirements

• Design, develop, train, and optimize machine learning models for real applications or use cases.
• Translate business and product requirements into scalable ML/AI solutions.
• Implement feature engineering, model selection, tuning, and evaluation techniques.
• Develop, and deploy ML models into production environments with high availability and performance.
• Build and maintain ML pipelines (training, validation, deployment, monitoring).
• Monitor model performance, data drift, and model decay; retrain models as needed.
• Ensure models meet reliability, scalability, and security standards.
• Collaborate with data engineering teams to ensure high-quality, reliable data pipelines.
• Participate in design and code reviews, ensuring engineering best practices.
• Optimize models for latency, throughput, and cost.
• Implement experimentation frameworks (A/B testing, offline evaluation).
• Apply responsible AI principles, including fairness, explainability, and governance where required.
• Experience working in agile, cross-functional teams.
• Experience with cloud platforms (AWS, Azure, or GCP) and managed ML services.
• Hands-on experience with MLOps tools (MLflow, Kubeflow, Airflow, SageMaker, Azure ML).
• Experience with big data technologies (Spark, Kafka, Databricks).
• Background in NLP, Computer Vision, or Generative AI.

Benefits

• Competitive salary
• Benefits package
• Opportunities for professional growth and development