Top AI & Machine Learning Jobs

Lead the design and evolution of an enterprise AI platform supporting experimentation through production. Manage and mentor AI engineers, establish MLOps and LLMOps standards, build cloud-native services for model serving and orchestration, and ensure scalability, reliability, security, governance, and cost efficiency. Partner with architecture, cloud, data, security, product, and data science teams to productionize AI and generative AI solutions while driving platform strategy, operational excellence, and engineering best practices.

Design, build, operate, and scale enterprise AI platforms across public and private clouds. Develop MLOps capabilities, CI/CD pipelines, infrastructure automation, observability, monitoring, governance, and AI deployment services. Support production machine learning and generative AI workloads, troubleshoot incidents, improve reliability and performance, collaborate with engineering, security, and governance teams, evaluate emerging technologies, and mentor peers.

Deploy into Mastercard Services engineering teams to write production software, resolve technical bottlenecks, accelerate critical roadmaps, and establish missing capabilities. Build production-grade AI assistants, agents, and RAG workflows; integrate evaluation, observability, governance, and responsible AI practices. Coach teams on AI-first development, transfer knowledge, create reusable reference implementations, and partner with architecture and platform teams to scale effective engineering patterns.

Design, build, operate, and scale enterprise AI platforms across public and private clouds. Develop MLOps, infrastructure automation, CI/CD, observability, governance, deployment, monitoring, and lifecycle-management capabilities for machine learning and generative AI workloads. Support production platforms, troubleshoot incidents, improve reliability and performance, collaborate with engineering, security, and governance teams, evaluate emerging technologies, and mentor peers.

Design, build, operate, and scale enterprise AI platforms across public and private clouds. Develop MLOps, automation, CI/CD, infrastructure, observability, monitoring, governance, and deployment capabilities for machine learning and generative AI workloads. Support production systems, incident response, troubleshooting, reliability, and lifecycle management. Collaborate with engineering, infrastructure, security, and governance teams, evaluate emerging technologies, contribute to architecture and strategy, and mentor peers.

Design, develop, and deploy machine learning models for ad targeting, ranking, and bidding optimization. Build personalization and recommendation systems at scale. Lead incrementality testing, attribution, and causal inference efforts. Partner with product, engineering, and analytics to deliver low-latency, production-ready ML pipelines and drive experimentation and measurement strategies across the AdTech ecosystem.

Lead and grow a global Product Data & Analytics team to deliver scalable analytics, predictive and prescriptive models, and data-driven insights. Manage projects, stakeholder relationships, and analytics strategy; deploy advanced ML solutions; ensure high-quality data products and reporting to support business decisions.

Designs scalable data science and analytics solutions for Mastercard Services. Develops KPIs, scorecards, dashboards, data pipelines, governance controls, and monitoring frameworks to improve platform effectiveness, data quality, operational efficiency, and business performance. Analyzes user behavior, workflows, integrations, and system risks; identifies automation and optimization opportunities; partners with business, operations, product, and technology teams; and presents actionable recommendations to leadership.

Lead the strategy, architecture, product development, and enterprise adoption of agentic AI systems for digital payments. Define roadmaps, agent workflows, KPIs, governance, safety guardrails, and human oversight. Partner with engineering, product, operations, legal, risk, and business teams to deliver scalable AI agents, automate workflows, conduct pilots, and drive adoption across markets.

Develop end-to-end data science and analytics solutions by integrating Salesforce, SQL Server, cloud, Databricks, financial, and other data sources. Build unified data assets, analytical platforms, models, and actionable insights supporting business performance, revenue optimization, product development, and go-to-market strategy. Lead analytics projects, collaborate with senior stakeholders, communicate findings to nontechnical audiences, and establish data analytics and infrastructure strategies.