Top AI & Machine Learning Jobs

Leads architecture and delivery of workflow automation, AI/ML pipelines, and cloud-native solutions across AWS, Azure, and GCP. Develops production-grade software, establishes Terraform and CI/CD standards, operationalizes model lifecycles, and promotes secure, resilient, cost-effective engineering practices. Scales enterprise AI-assisted development and SDLC automation across teams through governance, quality controls, responsible AI practices, and measurable delivery improvements.

Leads end-to-end development and production deployment of machine learning, generative AI, and agentic solutions for payments and banking. Responsibilities include problem framing, experimentation, evaluation, MLOps, LLMOps, governance, monitoring, scalable cloud architecture, security, and systems integration. The role establishes reusable AI capabilities, partners with cross-functional stakeholders, mentors technical teams, and communicates model outcomes and operational tradeoffs to technical and non-technical audiences.

Lead and mentor an agile engineering team to design, build, test, and operate secure, cloud-native production software. Provide technical direction, deliver high-quality code, drive product design decisions, and advocate firmwide engineering practices while applying AI/ML expertise.

Leads architecture, development, deployment, and optimization of enterprise LLM and GNN serving platforms across AWS, cloud, and on-premises environments. Establishes MLOps and LLMOps strategies, agentic AI engineering standards, automation, governance, observability, and operational practices. Optimizes inference for throughput and latency using Triton and vLLM, partners with data science and SRE teams, and influences senior stakeholders on secure, responsible AI adoption.

Lead applied AI/ML R&D to build GenAI and agentic AI tools that improve developer productivity, CI/CD, observability, and operational resilience. Design prototypes, establish reusable frameworks, advise engineering teams, and implement secure, compliant AI integrations and guardrails. Communicate findings to technical and non-technical stakeholders to drive enterprise adoption and strategy.

Own the analytics roadmap for a Consumer Banking customer pillar, leading measurement, experimentation, and analyses across growth, retention, pricing, servicing, and strategy. Translate complex business questions into executive-ready recommendations, influence cross-functional decisions, establish analytical standards, and mentor analytics talent. The role requires strong statistical, experimental, communication, visualization, and stakeholder-management skills.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage a team of data scientists and partner with engineering and business stakeholders to build, deploy, monitor, and govern models, establish best practices, and drive measurable operational impact.

Lead design, build, and deploy enterprise-scale AI solutions and multi-agent systems. Drive model lifecycle, monitoring, retraining, evaluation frameworks, semantic knowledge systems, and integration into operational workflows while communicating results to senior leadership.

Lead creation of an AI-first engineering capability for database products: design reusable frameworks, ensure secure production code, guide AI-enabled delivery, set governance and guardrails, influence senior stakeholders, and mentor engineers to scale cross-product adoption.

Lead design and deliver cloud-native microservices and AI/LLM-driven features. Architect scalable, secure systems, drive AI-assisted engineering practices, improve observability/automation, mentor teams, and integrate generative AI into business workflows.