Top Tech Jobs & Startup Jobs in NYC, NY

The role involves editing high-quality videos for social media and YouTube, focusing on both polished and raw content, storytelling, and brand consistency.

The Engineering Manager will lead and grow engineering teams working on core infrastructure, drive hiring, and ensure alignment in delivery between teams across disciplines.

Lead and scale mobile engineering across iOS and Android. Manage teams, drive strategy, ensure quality, and advocate for user experience.

Assist with secondary research, design and distribute surveys, analyze data with statistical tools, prepare reports and presentations, identify market trends and consumer preferences, and collaborate with teams to provide insights for projects.

The Acquisition Rep will handle lead follow-ups, negotiate property purchases, manage contracts, and support business growth with sales performance.

No responsibilities or duties are provided. The job description is a draft and only specifies the base pay range ($70,000-$80,000 per year).

The Senior Technical Support Engineer will provide advanced technical support, manage critical incidents, troubleshoot complex issues, and enhance product quality through root cause analysis.

Lead regional enterprise sales to hospitals and health systems: generate introductions, manage complex consultative deals through pipeline to close, negotiate contracts, transition clients to implementation, and support expansion and upsells while maintaining daily CRM hygiene (Salesforce).

Own and evolve the front-end architecture for a high-throughput, real-time trading app using Next.js, React, and TypeScript. Build pixel-accurate, accessible, responsive UIs under strict performance budgets; optimize rendering, state management, data flow, and bundle size for sub-second interactions. Integrate with REST and WebSocket APIs, lead end-to-end feature development, set engineering standards, mentor engineers, and contribute across the stack when needed.

Work on vision-language model development and infrastructure: improve VLM understanding, OCR and function-calling workflows, fine-tuning recipes, evaluation and robustness, and optimize training/serving pipelines. Own end-to-end projects from experiments to production-ready code, collaborating on scale, cost, and reliability.