Top Tech Jobs & Startup Jobs in NYC, NY

Conduct applied AI research and build foundation models across design, training, evaluation, validation, and deployment. Collaborate with data scientists, engineers, machine learning specialists, and product managers to deliver scalable AI-powered products. Research emerging methods, translate technical findings into business outcomes, develop platform and solution code, and contribute to technical reports or conference submissions. The role focuses on large deep learning models, optimization, fine-tuning, robustness, explainability, and research agenda ownership.

Lead product management for a financial core platform supporting accounts and transactions across Capital One. Build general platform capabilities, manage and mentor Product Managers, translate business and technology needs into data-backed recommendations, solve complex problems, and drive cross-functional alignment, innovation, customer value, and resilient digital financial services solutions.

Lead the architecture and evolution of enterprise developer telemetry and real-time data platforms. Build scalable streaming pipelines, AI inference capabilities, data lake solutions, observability frameworks, and privacy controls. Correlate AI engineering metrics with business outcomes while mentoring engineers, shaping technical strategy, evaluating build-versus-buy decisions, and contributing directly through prototypes, code patterns, and reusable data products.

Design, develop, deploy, and optimize production AI systems, including foundation models, LLM inference, agentic workflows, vector search, guardrails, and model evaluation. Lead architecture, cost-performance governance, technical reviews, and long-term roadmap development. Apply advanced optimization techniques to improve scalability, latency, throughput, hardware utilization, and inference costs while ensuring responsible AI standards. Mentor senior technical leaders and collaborate with engineers, scientists, technical program managers, and product managers.

Lead technical vision and software engineering strategy across complex domains. Design scalable, operable systems; modernize monoliths into microservices and event-driven platforms; define platform strategy and API standards; ensure implementation quality; and mentor engineers. The role requires hands-on technical contribution, cross-organizational collaboration, knowledge sharing, and leadership of modernization and best-practice initiatives.

Conduct applied AI research and develop foundation models from design through training, evaluation, validation, and production deployment. Lead research initiatives spanning large-scale deep learning, language models, optimization, fine-tuning, robustness, and explainability. Partner with data scientists, engineers, and product managers to translate research into scalable AI products, while guiding junior researchers and advancing research agendas.

Leads the virtual cards product strategy, roadmap, customer experience, growth initiatives, and go-to-market execution across web and mobile. Owns conversion and monthly active user growth, embeds virtual cards into onboarding and product launches, partners across business lines, and develops a high-performing product team. Requires at least five years of product management experience, with emphasis on digital products, user experience, and growth.

Lead an Applied AI data science team developing large-scale personalized recommendation and machine learning solutions. Partner with software engineers and product managers, build models through design, training, validation, and deployment, analyze massive structured and unstructured datasets, evaluate emerging technologies, and translate complex findings into business outcomes while developing team talent.

Leads product strategy and two product managers for regulatory and specialty back-office servicing experiences. Owns a multi-year roadmap focused on AI-driven automation, cloud data, compliant workflows, and improved customer and agent experiences. Partners with Risk, Legal, Compliance, Operations, Business Analysis, and technology teams to scale automated servicing capabilities across lines of business.

Leads full-stack engineering teams, technology portfolios, and large-scale cloud-native initiatives. Responsibilities include setting technical strategy, mentoring engineering leaders, driving architectural decisions, managing multi-team Agile programs, defining technology roadmaps, and aligning engineering execution with business goals. The role involves designing distributed systems, supporting regulatory needs, evaluating code, developing talent and succession plans, and guiding teams using modern programming languages, cloud platforms, databases, containers, and open-source technologies.