Senior Machine Learning Engineer

About the role

This role focuses on the end-to-end lifecycle of AI and machine learning solutions, from ideation and development to deployment and ongoing maintenance of production-grade systems. Reporting to the AI Solutions Architect and partnering closely with the Chief Product Officer and Chief Innovation Officer, the Senior Machine Learning Engineer will play an important role in building scalable, robust, and efficient AI-driven software solutions. This individual must be able to bridge exploratory projects with production systems, ensuring seamless transitions and operational excellence.

What you'll do

• AI Solution Development and Deployment:
• • Collaborate with cross-functional teams to define and design AI solutions aligned with business objectives.
  • Build, deploy, and maintain production-grade machine learning models and systems that drive efficiency and innovation across multiple departments.
  • Ensure AI solutions meet performance, scalability, and reliability standards in a production environment.
• Model Optimization and Maintenance:
• • Continuously improve machine learning models through fine-tuning, retraining, and incorporating new data and feedback.
  • Monitor and optimize the performance of deployed models and systems, implementing updates and resolving issues proactively.
  • Work with the AI Solutions Architect to develop pipelines for automated retraining, testing, and deployment of AI models.
• Cloud Infrastructure and Integration:
• • Leverage cloud platforms (e.g., AWS, Azure, Google Cloud) for model deployment, orchestration, and monitoring.
  • Implement and manage robust infrastructure to support AI applications, ensuring scalability and fault tolerance.
• Pipeline Development and Data Engineering:
• • Develop and maintain data pipelines for efficient data ingestion, preprocessing, and feature engineering.
  • Support integration of AI models into existing software systems, collaborating with product and engineering teams.
• Exploratory Analysis and Proof of Concept Development:
• • Conduct exploratory analyses to identify opportunities for AI innovation.
  • Design and prototype solutions, validating feasibility through proof of concept (PoC) projects.
  • Work closely with cross-functional stakeholders to develop experimental projects and transition them into fully developed systems.
• Performance Monitoring and Troubleshooting:
• • Implement monitoring tools to track model performance, system reliability, and data integrity.
  • Diagnose and address issues in deployed solutions, ensuring minimal downtime and consistent results.
• Documentation and Compliance:
• • Maintain comprehensive documentation of workflows, models, and system designs to support transparency and collaboration.
  • Adhere and enforce existing organizational standards.

Qualifications

• 3+ years of experience in ML/AI development including production-environment deployments
• Bachelor's degree or higher in a relevant field.
• Proficiency in Python and its machine learning frameworks (e.g., TensorFlow, PyTorch, scikit-learn).
• Hands-on experience with data pipeline development, including data ingestion, preprocessing, and feature engineering.
• Experience with large language models (LLMs) and natural language processing (NLP), including prompt engineering and fine-tuning techniques.
• Knowledge of advanced methods such as Retrieval-Augmented Generation (RAG) and platforms like OpenAI or Hugging Face.
• Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud).
• Excellent problem-solving skills and ability to troubleshoot and optimize complex AI systems.
• Strong communication skills to work effectively with technical and non-technical stakeholders.