Top Tech Jobs & Startup Jobs in NYC, NY

Develop and deploy high-scale machine learning and personalization models for Capital One’s web and mobile experiences. Responsibilities include researching recommendation systems, foundation models, reinforcement learning, causal inference, and transformer architectures; analyzing large datasets; building models through training, evaluation, validation, and implementation; and collaborating with data scientists, engineers, and product managers.

Build and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Design multi-model orchestration pipelines, improve model cost, latency, throughput, and scalability, establish AI governance standards, lead technical reviews, and mentor senior AI engineering staff. Collaborate with engineers, scientists, technical program managers, and product managers to deliver responsible AI capabilities.

Design, develop, deploy, and support production AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize AI platforms for cost, latency, throughput, scalability, and hardware utilization. Lead architecture and governance reviews, shape long-term platform roadmaps, establish engineering standards, and mentor senior AI engineers across the organization.

Lead a greenfield enterprise product initiative for third-party management across Capital One’s supplier network. Drive product strategy, customer-centered solutions, technology delivery, risk mitigation, cross-functional alignment, and transformational outcomes for Enterprise Services & Supplier Product, Risk & Operations.

Build and optimize foundational AI systems, including LLM training and inference, agentic workflows, vector search, guardrails, evaluation, and observability. Partner with engineering, research, product, and program teams to deliver scalable AI products. Lead model and infrastructure optimization for cost, latency, throughput, and hardware utilization; establish governance and engineering standards; contribute to technical roadmaps; and mentor senior AI leaders.

Leads large-scale technical programs and platform initiatives focused on resiliency, reliability, scalability, and operational efficiency. Establishes TPM strategies, operating models, maturity frameworks, and tooling; drives roadmaps, architectural alignment, investment planning, and cross-team delivery. Acts as an executive escalation point, manages risks and tradeoffs, defines measurable outcomes, and builds TPM capability across engineering organizations.

Design, develop, deploy, and support foundational AI systems, including foundation-model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. Optimize distributed AI systems for cost, latency, throughput, scalability, and hardware utilization. Own complex architectures, define reliability objectives, lead technical reviews, ensure security and compliance, contribute to long-term AI roadmaps, and mentor engineering teams.

Design, develop, deploy, and optimize foundational AI systems, including LLM inference, foundation model training, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Lead architecture, cost-performance optimization, technical standards, and roadmap development for scalable production AI platforms. Partner with researchers, engineers, technical program managers, and product managers while mentoring senior technical staff and advancing responsible AI practices.

Own and drive major portions of the Capital One Travel product roadmap. Lead cross-functional teams to improve booking funnels, expand hotel offerings, and build post-booking disruption services. Apply human-centered, business-focused, and technology-driven product practices to deliver innovative, customer-centric travel experiences and measurable business outcomes.

Designs, develops, deploys, and supports scalable AI systems, including foundation model training, LLM inference, agentic workflows, similarity search, guardrails, evaluation, governance, and observability. The role optimizes model performance, GPU/TPU utilization, latency, throughput, and cost; owns complex AI architecture; defines reliability objectives; leads technical reviews; and mentors engineering teams.