Artificial Intelligence Engineer

Responsibilities

Design, develop, and deploy machine learning and Al models to support advanced analytics and business intelligence initiatives.

Build and optimize end-to-end machine learning pipelines, including data preprocessing, feature engineering, model training, and model evaluation.

Collaborate with data engineers to ensure data quality, scalability, and efficient data access for Al/ML workloads.

Partner with business analysts and stakeholders to translate business problems into ML/Al solutions and measurable outcomes.

Implement Al model monitoring, validation, and governance practices to ensure production performance and compliance.

Stay current with emerging Al/ML technologies, frameworks (TensorFlow, PyTorch, scikit-learn), and best practices.

Support experimentation, POCs, and feasibility studies for new Al/ML capabilities.

Document models, algorithms, and technical implementations for knowledge transfer and audit trails.

Qualifications

Advanced proficiency in Python, R, or similar languages; familiarity with ML frameworks (TensorFlow, PyTorch, scikit-learn).

Strong understanding of machine learning algorithms, statistical modeling, and data science fundamentals.

Experience with cloud ML platforms (Azure ML, AWS SageMaker, Google Vertex Al) and model deployment pipelines.

Knowledge of data warehouse/lake architecture and SQL for efficient data access.

Familiarity with ML Ops practices, model versioning, and CI/CD for machine learning.

Strong problem-solving skills and experience translating business requirements into technical solutions.