Senior AI Engineer

Day in the life:

• Design and develop AI solutions that address real-world business challenges, ensuring alignment with strategic objectives and measurable outcomes.
• Work with large-scale structured and unstructured datasets, leveraging modern data frameworks, tools, and platforms.
• Establish and maintain robust standards for data security, privacy, and regulatory compliance across all AI and data workflows.
• Collaborate closely with cross-functional teams to gather requirements, share insights, and deliver high-impact solutions.
• Monitor and maintain production AI systems to ensure continued accuracy, scalability, and reliability over time.
• Stay up to date with the latest advancements in AI, machine learning, and data engineering, and apply them where relevant.
• Write clean, well-documented, and maintainable code, and actively contribute to team best practices and technical documentation.

You'll be perfect for the role if you have:

• Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
• Strong programming skills in Python (preferred) and experience with AI/ML libraries such as TensorFlow, PyTorch, scikit-learn, or Hugging Face
• Experience designing and deploying machine learning models and AI systems in production environments
• Familiarity with modern data platforms and cloud services (e.g., Azure, AWS, GCP), including AutoML and MLflow
• Proficiency with data processing tools and frameworks (e.g., Spark, Pandas, SQL) and working with both structured and unstructured data
• Experience with Generative AI technologies, including prompt engineering, vector databases, and RAG (Retrieval-Augmented Generation) pipelines
• Solid understanding of data security, privacy, and compliance principles, with experience implementing these in real-world projects
• Strong problem-solving skills and ability to translate complex business problems into technical solutions
• Excellent communication and collaboration skills, with the ability to work effectively across technical and non-technical teams
• Experience with version control (e.g., Git) and agile development practices
  • Enthusiasm for learning and applying emerging technologies in AI and machine learning