MLOps Engineering Director

2 days ago

Gurgaon, Haryana, India Mastercard Full time ₹ 12,00,000 - ₹ 36,00,000 per year

Title and Summary

  • MLOps Engineering DirectorThe Security Solutions Data Science team is responsible for creating Artificial Intelligence (AI) and Machine Learning (ML) models backing its flagship product
  • The models generated are production ready and created to back specific products in Mastercards authentication and authorization networks
  • The Data Science team is also responsible for developing automated processes for creating models covering all modeling steps, from data extraction up to delivery
  • In addition, the processes must be designed to scale, to be repeatable, resilient, and industrialized
  • Services within Mastercard is responsible for acquiring, engaging, and retaining customers by managing fraud and risk, enhancing cybersecurity, and improving the digital payments experience
  • We provide value-added services and leverage expertise, data-driven insights, and execution
  • You will be joining a team of Data Scientists and engineers working on innovative AI and ML fraud detection
  • Our innovative cross-channel AI solutions are applied in Fortune 500 companies in industries such as fin-tech and payments processing
  • We are pursuing a highly motivated individual with strong problem-solving skills to take on the challenge of structuring and engineering data and cutting-edge AI model evaluation and reporting processes
  • As a Director, MLOps Engineer, you will:Oversee the administration of Databricks clusters and workspaces
  • Bring MLOps expertise to the table, namely within the scope of, but not limited to: o Model monitoring o Feature catalogo Experiment Tracking
  • o CI/CD pipelines to gatekeep model lifecycle from development to production Own and maintain MLOps solutions either by leveraging open-sourced solutions or with a 3rd party vendor
  • Build and maintain various executive dashboards that reflect metrics, model build, deploy, and run phases
  • Manage a team of MLOps engineers

[All About You]

  • Masters degree in computer science, software engineering, or a similar field
  • Strong experience with Databricks and ability to architect scalable DE pipelines
  • Strong experience with Spark
  • Experience in cloud technologies and operations
  • Experience supporting APIs and Cloud technologies
  • Experience with MLOps solutions like MLFlow, Comet, WandB, or other similar frameworks
  • Experience with performing data analysis, data observability, data ingestion and data integration
  • Solid DevOps, SRE, or general systems engineering experience
  • Hands-on experience in industry standard CI/CD tools like Git/BitBucket, Jenkins,Maven, Artifactory, and Chef
  • Experience architecting and implementing data governance processes and tooling (such as datacatalogs, lineage tools, role-based access control, PII handling)
  • Strong coding ability in Python or other languages like Java, and C++, plus a solid grasp of SQL fundamentals
  • Systematic problem-solving approach, coupled with strong communication skills and a sense ofownership and drive

Nice to have:

  • SQL tuning experience
  • Strong automation experience Strong Data Observability experience
  • Operations experience in supporting highly scalable systems
  • Self-Motivating and creatively solves software problems and effectively keep the lights on for modeling systems

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