Top AI & Machine Learning Jobs

Leads the architecture, development, deployment, and lifecycle management of enterprise AI, machine learning, generative AI, and agentic AI platforms. Establishes AI engineering standards, MLOps and AgenticOps practices, cloud-native architectures, governance, security, and operational excellence. Partners with architecture, security, product, data science, and infrastructure teams to define roadmaps, evaluates emerging technologies, mentors engineers, and drives production adoption of scalable AI capabilities.

Lead the design and development of scalable cloud-native data platforms and batch or real-time pipelines supporting AI, machine learning, and Generative AI. Build infrastructure for feature engineering, model training, inference, LLMs, RAG, embeddings, and vector databases. Ensure data quality, governance, security, observability, reliability, and cost efficiency while enabling MLOps and AgenticOps capabilities across enterprise AI initiatives.

Manage strategy roadmaps and execution for data science initiatives involving data pipelines, AI tooling, model monitoring, and development stacks. Coordinate data science, engineering, product, and leadership teams; align priorities, dependencies, risks, timelines, and trade-offs; communicate status to stakeholders; facilitate planning and retrospectives; and drive continuous improvement across complex, matrixed programs.

Leads technical program management for Mastercard’s Security Solutions Data Science team. Develops roadmaps, execution plans, milestones, and measurable outcomes; coordinates data scientists, engineers, product managers, and senior leaders; manages dependencies, risks, trade-offs, and escalations; tracks delivery across data pipelines, AI tooling, model monitoring, and development-stack initiatives; communicates program status and technical decisions; and drives retrospectives and continuous improvement.

Design, build, deploy, and operate enterprise AI, machine learning, generative AI, and agentic AI systems. Productionize prototypes into scalable platforms, develop end-to-end ML pipelines and LLM applications using RAG and vector databases, and implement MLOps and AgenticOps practices. Architect cloud-native services with Kubernetes and microservices, optimize reliability and performance, and ensure security, privacy, compliance, governance, and responsible AI standards. Collaborate with technical and business stakeholders on reusable AI capabilities and strategic roadmaps.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, model serving/inference, and MLOps practices. Collaborate with product, data, and engineering partners, perform performance tuning, and ensure model reliability, monitoring, and lifecycle management.

Design, build, and deploy transformer-based and generative AI models into production. Develop training workflows, data pipelines, feature engineering, and model serving. Implement MLOps best practices (tracking, versioning, testing, monitoring), collaborate with product and engineering teams, perform performance tuning, and support production model troubleshooting.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, training workflows, model serving and inference, apply MLOps practices, monitor performance, collaborate with product and engineering teams, and support troubleshooting and optimization.

Lead product strategy and execution for agentic AI reconciliation and an enterprise API platform. Define roadmaps, commercialize products, ensure regulatory compliance and reliability, engage clients, and build a high-performing PM team across engineering, data science, compliance, and commercial stakeholders.

Design, build, and deploy transformer-based and generative AI models into production. Develop data pipelines, feature engineering, training workflows, and model serving. Apply MLOps practices, collaborate with product and engineering teams, and support production troubleshooting and performance tuning.