Machine Learning Engineer

Purpose:

• Designs, develops, and deploys machine learning models and pipelines to support data-driven applications and services across the AI portfolio

Responsibilities:

• Design and develop machine learning models to solve business problems; Build and maintain scalable ML pipelines from data preprocessing to deployment.
• Collaborate with data scientists and engineers to integrate models into production systems
• Monitor and optimize model performance in real-time environments; Implement versioning, reproducibility, and tracking of ML experiments
• Contribute to code reviews and ML framework standardization

Requirements:

• Degree in Computing, Engineering, Computer Science, Machine Learning or AI with 3 - 5 years of experience in ML model development and deployment.
• Proficiency in Python, TensorFlow, PyTorch, or Scikit-learn; Experience with MLOps tools (MLflow, Kubeflow, SageMaker, etc.)
• Strong knowledge of data structures, software engineering, and cloud ML infrastructure
• Understanding of CI/CD pipelines and containerized deployments (e.g., Docker, Kubernetes)
• Strong problem-solving and debugging skills; Collaboration with cross-functional teams
• Clear documentation and communication of model behavior