
Lead AI Engineer
1 week ago
Responsibilities
Lead the E2E design and development of AI-powered microservices, focusing on modularity, scalability, and reusability, to support various business units and applicationsDrive the transition of AI models from notebook-based PoCs and experimental phases into hardened, production-gradeponents and services, ensuring performance, reliability, and maintainability
Design and implement robust APIs for AI microservices, facilitating seamless integration with existing Mastercard platforms and external systems.
Identify and address performance bottlenecks within AI microservices and their underlying infrastructure, optimizing for latency, throughput, and cost-efficiency.
Work closely with data scientists, MLOps engineers, and product teams to translate business requirements into technical specifications for AI services. Mentor junior engineers on best practices for AI software development and scaling
Implement rigorous testing strategies, including unit, integration, and performance testing, to ensure the quality, accuracy, and stability of deployed AI microservices
Research and evaluate new technologies, frameworks, and methodologies related to AI software development, microservices, and large-scale data processing to continuously improve our capabilities
Ensure all AI microservices adhere to Mastercard's security standards,pliance policies, and ethical AI principles
Qualifications
Education: Bachelor's degree inputer Science, Engineering, Data Science, or a related technical field. Master's degree preferred
Experience: Minimum of 8+ years of experience in software development, with at least 4 years specifically focused on building and deploying AI/ML-powered applications or microservices in production environments
Technical Skills:
Strong proficiency in Python
Extensive experience in designing, developing, and deploying RESTful APIs and microservices
Proven experience in scaling machine learning models from prototype to production, including familiarity with feature stores, model registries, and inference patterns
Solid understanding of the AI/ML lifecycle, from data preparation and model training to deployment and monitoring
Experience with cloud platforms and their relevantpute, storage, and AI/ML services
Proficiency with containerization technologies
Familiarity with CI/CD pipelines for automated testing and deployment of software and AI models
Experience with distributedputing frameworks (, Spark, Dask) is a plus
Understanding of dataernance, data quality, and data security principles relevant to AI/ML applications
Excellentmunication, interpersonal, and stakeholder management skills, with the ability to effectively articulateplex technical concepts to both technical and non-technical audiences
Proven ability to lead technical initiatives, drive cross-functional projects, and influence oues within a fast-paced environment
#AI
Corporate Security Responsibility
All activities involving access to Mastercard assets, information, and networkses with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
Abide by Mastercard's security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation or breach, and Job ID R-257248
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