Top Tech Jobs & Startup Jobs in NYC, NY

Conduct applied research in AI safety and multimodal systems, developing foundation models across design, training, evaluation, validation, and deployment. Collaborate with data scientists, engineers, and product managers to deliver AI products at scale. Research areas include large language models, optimization, self-supervised learning, robustness, explainability, red teaming, safety guardrails, and multimodal vulnerability assessment. Publish findings, reproduce research, and independently pursue impactful research agendas.

Develop and deploy scalable optimization, simulation, and machine learning models for banking decision systems. Translate complex business challenges into mathematical problems, build production-grade algorithms using Python and optimization solvers, design experiments, and integrate modeling solutions with software systems. Collaborate with Product, Engineering, and Business teams to improve customer experiences, risk policies, and operational decision-making.

Leads product strategy and execution for Capital One’s global payment network, including digital wallets, tokenization, click-to-pay, issuer relationships, authorizations, settlement, disputes, pricing, and go-to-market. Drives scalable payment experiences, innovation, cross-functional alignment, customer-centered solutions, technology adoption, and AI integration across the organization.

Design, develop, deploy, and support large-scale AI systems, including foundation model training, LLM inference, agentic workflows, vector search, guardrails, evaluation, governance, and observability. Optimize models and infrastructure for cost, latency, throughput, and hardware utilization. Architect multi-model orchestration pipelines, establish AI engineering standards, lead technical reviews, and mentor senior AI engineers.

Conduct applied AI research and build foundation models through design, training, evaluation, validation, and implementation. Collaborate with data scientists, engineers, and product managers to deliver scalable AI products. Research emerging methods, develop model and platform code, translate technical findings into business outcomes, and contribute to internal reports and conference publications. The role may focus on large language models, training and inference optimization, or fine-tuning.

Leads data analysis strategy, modeling, reporting, experimentation, and process improvement using large and complex datasets. Manages and mentors junior analysts, collaborates across business units, supports business intelligence initiatives, and contributes to data products, dashboards, testing frameworks, and operational efficiency improvements. The role involves programming, database analysis, strategic project ownership, and stakeholder consultation in a hybrid environment.

Develops insight-driven product marketing strategies for business cards and payment products, including positioning, go-to-market planning, campaign optimization, testing, messaging, and new feature launches. Partners with insights, creative, product, digital, and channel teams; manages creative development; analyzes customer and campaign data; monitors competitors; and translates findings into actionable marketing plans and business impact.

Lead data science and model risk initiatives by partnering with data scientists, engineers, and product managers. Build, evaluate, validate, and implement machine learning models using large-scale numeric and textual data. Apply statistical methods, backtesting, and model-risk expertise while translating complex analyses into business outcomes. Responsibilities also include researching emerging technologies, improving decision-making, and developing talent.

Leads full-stack engineering projects and developer teams building large-scale, cloud-native distributed systems. Responsibilities include architecture, implementation, technical strategy, platform roadmaps, regulatory solutions, mentoring, observability, reliability, and performance optimization. The role uses modern programming languages, cloud platforms, databases, containers, APIs, CI/CD, infrastructure as code, and AI-assisted development tools while collaborating with product managers, architects, and engineering leaders.

Leads customer data product strategy to improve segmentation, personalization, customer value, marketing, servicing, and credit performance. Develops metrics, models, business requirements, product and pricing strategies, and go-to-market initiatives. Oversees concurrent projects, partners cross-functionally, and may manage analysts. Requires strong quantitative and qualitative analysis, executive communication, people leadership, product development, financial modeling, and strategic decision-making.