Job
Description
Role Overview: You are seeking a highly experienced and innovative Senior AI Engineer to join the rapidly expanding AI/ML team at CGI. With 7+ years of hands-on experience, you will play a crucial role in the end-to-end lifecycle of AI/ML solutions, from research and prototyping to developing, deploying, and maintaining production-grade intelligent systems. By collaborating closely with data scientists, product managers, and software engineers, you will drive the adoption of cutting-edge AI technologies across platforms. Key Responsibilities: - Design, develop, train, and optimize robust and scalable machine learning models (e.g., deep learning, classical ML algorithms) for various applications. - Build and maintain end-to-end MLOps pipelines for model deployment, monitoring, versioning, and retraining, ensuring reliability and performance in production environments. - Work with large, complex datasets, perform data cleaning, feature engineering, and data pipeline development to prepare data for model training and inference. - Explore and evaluate new AI/ML technologies, algorithms, and research papers to identify opportunities for innovation and competitive advantage. Rapidly prototype and test new ideas. - Optimize AI/ML models and inference systems for speed, efficiency, and resource utilization. - Partner closely with Data Scientists and Software Engineers to transition research prototypes into production-ready solutions, integrate AI models into existing products and platforms, and communicate complex AI concepts to technical and non-technical stakeholders. - Write clean, maintainable, and well-documented code, implement software engineering best practices within the AI/ML lifecycle, and implement robust monitoring for model performance, data drift, and system health in production. Qualifications Required: Must-Have Skills: - 7+ years of hands-on experience as an AI Engineer, Machine Learning Engineer, or a similar role focused on building and deploying AI/ML solutions. - Strong proficiency in Python and its relevant ML/data science libraries (e.g., NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch). - Extensive experience with at least one major deep learning framework such as TensorFlow, PyTorch, or Keras. - Solid understanding of machine learning principles, algorithms (e.g., regression, classification, clustering, ensemble methods), and statistical modeling. - Experience with cloud platforms (e.g., AWS, Azure, GCP) and their AI/ML services (e.g., SageMaker, Azure ML, Vertex AI). - Proven experience with MLOps concepts and tools for model lifecycle management (e.g., MLflow, Kubeflow, Sagemaker MLOps, Azure ML Pipelines). - Strong SQL skills for data manipulation, analysis, and feature extraction from relational databases. - Experience with data preprocessing, feature engineering, and handling large datasets. Good-to-Have Skills: - Familiarity with software development best practices including version control (Git), code reviews, and CI/CD.,
