Top Tech Jobs & Startup Jobs in NYC, NY

Leads full-stack software engineering initiatives using cloud technologies, distributed microservices, databases, APIs, and modern programming languages. Provides technical direction across Agile teams, mentors engineers, partners with architects and product managers, establishes engineering standards, improves system performance, reduces technical debt, and evaluates emerging technologies including AI-based development tools.

Conduct applied research on large language models, training optimization, and fine-tuning. Design, train, evaluate, validate, and deploy AI foundation models using PyTorch, AWS, Hugging Face, and Lightning. Lead research initiatives across data science, engineering, and product teams, translating advances into scalable production systems. Candidates should have advanced academic training and experience with large-scale deep learning, model optimization, self-supervised learning, robustness, explainability, or RLHF, plus a record of impactful research and publications.

Lead data science and NLP initiatives for AI-powered products, partnering with engineers, machine learning specialists, and product managers. Build, fine-tune, evaluate, validate, and operationalize large language and machine learning models at scale. Apply advanced NLP, deep learning, and model training techniques while supporting model risk compliance. Translate technical findings into business outcomes and develop team talent.

Leads regional technical payment-acceptance operations across Latin America, the Caribbean, and Mexico. Manages a distributed team, translates global strategy into market plans, diagnoses and remediates acceptance failures, and coordinates cross-functional initiatives with payment ecosystem partners. Establishes monitoring, KPIs, controls, playbooks, and governance while influencing senior stakeholders and developing team capability. Requires fluent Spanish and English, extensive payment operations experience, and approximately 15% travel.

Lead data science for US Card customer management by partnering with data scientists, engineers, product managers, and business teams. Build, validate, and implement machine learning models using large-scale numeric and textual data. Apply statistical modeling, clustering, classification, sentiment analysis, time series, and deep learning to generate customer insights and forecasts. Translate technical findings into business outcomes while contributing to innovation, stakeholder collaboration, and talent development.

Build and lead full-stack software engineering solutions using distributed systems, microservices, cloud platforms, and modern open-source technologies. Responsibilities include leading technology projects and developers, defining architectures and APIs, mentoring engineers, improving system performance, reducing technical debt, establishing engineering standards, and delivering scalable solutions with Agile teams. The role requires extensive experience with programming languages, databases, cloud infrastructure, CI/CD, testing, version control, and technical leadership.

Leads product analytics for Retail Bank growth, using SQL, Python, R, experimentation, causal inference, statistical modeling, segmentation, and data storytelling. Partners with Product, Engineering, Finance, and Research to shape roadmaps, prioritize opportunities, establish KPI standards, and influence investment and product decisions.

Leads full-stack software engineering projects and developer teams building cloud-based, distributed microservices and customer-facing systems. Responsibilities include designing service boundaries, developing APIs, improving system performance, reducing technical debt, establishing engineering standards, mentoring engineers, and influencing technology strategy. The role uses modern programming languages, databases, container orchestration, cloud platforms, CI/CD, infrastructure as code, automated testing, observability, and AI-based development tools.

Leads enterprise analytical-tool validation, including framework refinement, project execution, methodology risk assessment, technical research, prototyping, and validation reporting. Partners with cross-functional leaders to influence business strategy, solves complex analytical problems, and coaches junior staff. Requires substantial data analytics, open-source technology, statistical modeling, and people-management experience.

Leads engineering projects and developers building cloud-based, AI-powered risk management solutions. Designs distributed microservices and full-stack systems, establishes technical standards, partners with architects and product managers, improves system performance, reduces technical debt, and mentors engineers. The role uses AWS technologies, modern programming languages, databases, APIs, CI/CD, infrastructure as code, automated testing, and observability within Agile teams.