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The CNPF Data & AI organisation is looking for an AI Engineer II to support the build and operation of applied AI solutions. This role is ideal for someone early in their AI engineering career who has moved beyond junior-level work and is ready to take on independent delivery ownership with guidance from senior engineers. You will work closely with AI engineers, data scientists, and software engineers to build, deploy, and operate production AI systems. The focus of this role is execution: writing quality code, shipping features, and learning how to build reliable, scalable AI systems in a real production environment.
Job Responsibility:
Build and maintain AI and ML-enabled services under guidance from senior engineers
Support deployment and operation of ML models in production environments
Participate in data preparation, feature engineering, and experimentation workflows
Contribute to ML pipelines, inference services, and batch or real-time data flows
Debug, monitor, and improve existing AI systems to ensure reliability and performance
Collaborate with data scientists to translate models into working production solutions
Follow engineering best practices for testing, documentation, and version control
Learn and apply Mastercard standards for security, governance, and responsible AI
Requirements:
Experience working as an AI engineer, ML engineer, or software engineer on data- or ML-driven systems
Working knowledge of Python and common data and ML libraries
Basic understanding of how ML models move from development into production
Familiarity with data pipelines, APIs, and foundational distributed systems concepts
Comfortable working with guidance on ambiguous problems and learning through delivery
Strong interest in growing technical depth in AI engineering and ML operations
Clear written and verbal communication skills and a collaborative mindset
Nice to have:
Exposure to real production AI or ML systems rather than only academic or demo work
Experience supporting model deployment, monitoring, or inference services
Curiosity about agentic or LLM-based systems, even if experience is still early
Strong ownership mindset and willingness to learn from production challenges
Solid engineering fundamentals and eagerness to grow into senior AI engineering roles