Top AI & Machine Learning Jobs

Embed with Services teams to write production code, remove delivery bottlenecks, and accelerate roadmaps. Design and deploy production-grade AI solutions (LLMs, agents, RAG), improve AI-enabled SDLC practices, coach teams, transfer capabilities, and deliver reusable patterns and reference implementations that scale across the organization.

Embed with Services teams to write production code, unblock delivery, and deploy AI solutions (LLMs, agents, RAG). Provide surge engineering capacity, clear architectural and delivery bottlenecks, coach teams in AI-first practices, and deliver reusable patterns and enablement.

Embed with Services teams as a hands-on principal engineer to write production code, unblock delivery, deploy AI/agent solutions (LLMs, RAG), coach teams, improve CI/CD and cloud-native architectures, and deliver reusable AI patterns and enablement.

Embed with Services teams as a hands-on principal engineer to write production code, remove technical bottlenecks, deliver AI-driven solutions (LLMs, agents, RAG), upskill teams, and create reusable AI patterns and tooling to scale across the organization.

Embed as a hands-on principal engineer to write production code, unblock delivery, and accelerate Services programs. Deploy AI-first solutions (LLMs, agents, RAG), coach teams, improve CI/CD and cloud-native practices, and deliver reusable patterns and enablement.

Lead regional commercialisation and deployment of AI-powered SME solutions across APAC. Act as APAC subject-matter expert on LLMs and agentic AI, translate customer needs into product requirements, run pilots and go-to-market strategies, and drive adoption through cross-functional collaboration with product, engineering, sales, and partners.

Lead the design and implementation of agentic AI and LLM applications within Mastercard's Operational Intelligence team, focusing on backend and production-scale solutions. Mentor engineers and ensure high reliability and observability of systems. Develop integration between AI platforms and enterprise data services.

Develop and productionize ML/AI models and scalable data science capabilities for merchant risk assessment. Work on data extraction, feature engineering, entity resolution, prototyping models, validating and monitoring performance, and building Databricks/Spark-based workflows in collaboration with Data Science, Product, and Engineering teams.

Lead a data science team to design and deliver merchant registry and profiling ML capabilities for onboarding and monitoring. Define strategy, guide model development and validation, promote reusable data assets, partner with Product and Engineering, drive Agile delivery, hire and mentor team members, and communicate impact to senior leadership to scale production ML systems on modern cloud/data platforms.

Lead and grow a data science team to build merchant registry and profiling capabilities. Define strategy, drive ML model development and deployment at scale, establish best practices, partner with Product and Engineering, and deliver measurable business outcomes while promoting reusable assets and Agile delivery.