Senior Group Technical Architect

Role overview

Responsibilities

• Design and maintain scalable machine learning and deep learning solutions using Python.
• Build, train, evaluate, and deploy models for predictive analytics, forecasting, recommendations, NLP, or computer vision.
• Collaborate with data engineers, business analysts, product owners, and stakeholders to define AI/ML solutions.
• Participate in Agile ceremonies, including sprint planning, daily stand-ups, retrospectives, and grooming.
• Analyze model performance and work with teams to improve solution effectiveness.
• Maintain model documentation, experiment tracking, feature engineering workflows, and deployment reports.
• Integrate models with CI/CD and MLOps pipelines for continuous deployment and monitoring.
• Ensure model accuracy, scalability, reliability, and governance across business applications.
• Perform data analysis, feature engineering, model validation, and performance optimization.
• Contribute to AI/ML best practices, model lifecycle management, and framework enhancements.

Mandatory skills

• Hands-on machine learning model development and deployment experience, including supervised and unsupervised algorithms.
• Experience with feature engineering, model evaluation, performance optimization, statistical methods, and predictive analytics.
• Deep learning framework experience with TensorFlow, PyTorch, or Keras.
• Experience developing NLP, computer vision, or generative AI solutions.
• Experience with MLflow or a similar MLOps platform and knowledge of model versioning, experiment tracking, deployment, and monitoring.
• Strong Python proficiency and experience with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.

Advantageous experience

• Generative AI, LLMs, RAG, or Agentic AI frameworks are good to have.
• Cloud platform experience with GCP, Azure, or AWS is good to have.
• Big data technologies such as Spark or Databricks are good to have.
• Vector databases, semantic search, Docker, and CI/CD tools such as Jenkins, Azure DevOps, or GitHub Actions are good to have.
• Experience with enterprise-scale AI/ML applications is good to have.