Top Tech Jobs & Startup Jobs

Lead end-to-end machine learning systems across data, training, fine-tuning, evaluation, inference, and deployment. Build scalable large-model pipelines, optimize GPU-based inference for latency, cost, memory, and reliability, and establish production monitoring and continuous improvement infrastructure. Partner with research and application engineering to translate model capabilities into reliable product improvements while supporting team delivery and maintaining high standards for correctness and quality.

Own product areas for an AI neobank across financial services such as payments, savings, investing, insurance, and travel. Define user problems, roadmaps, metrics, scope, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial journeys; launch features; monitor performance; and iterate using data, research, feedback, and production issues.

Own the company-wide performance management and OKR frameworks, lead planning and review cycles, and develop scalable people processes. Analyze organizational data, build performance dashboards, define HR system requirements, and partner with leaders to improve execution, accountability, career development, and employee experience. Support performance reviews, calibration, promotions, culture initiatives, and strategic people projects in a fast-growing environment.

Leads application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Designs reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Builds APIs connecting AI capabilities to user experiences, makes architecture and scalability trade-offs, establishes observability and testing, and leads a small senior engineering team through technical reviews and mentorship.

Lead the architecture and hands-on development of reliable AI-powered email applications across backend, mobile, and desktop platforms. Design orchestration, state management, tool use, retries, fallbacks, and failure handling for long-running workflows. Build production APIs, improve observability and reliability, make trade-offs involving latency, cost, security, and user experience, and lead a small senior engineering team through technical reviews, mentorship, and execution.

Owns end-to-end machine learning systems across data, training, evaluation, inference, deployment, and monitoring. Builds large-model training and fine-tuning pipelines, evaluation frameworks, high-performance GPU inference systems, and reliable production infrastructure. Partners with research and application engineering to convert model capabilities into measurable product improvements. Provides hands-on technical leadership, makes pragmatic trade-offs, and ensures ML systems are scalable, efficient, safe, reliable, and production-ready.

Lead application engineering for an AI-powered email product across backend, mobile, and desktop platforms. Design reliable AI workflows involving orchestration, state, tool use, retries, fallbacks, and failure handling. Build APIs connecting AI capabilities to product experiences, make architectural trade-offs, establish observability and operational excellence, and lead a small team of senior engineers through hands-on technical mentorship and code development.

Own AI Investing product areas across financial services, defining user problems, product scope, metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Launch features, monitor performance, incorporate user feedback and research, and drive continuous iteration while balancing speed, customer experience, business impact, compliance, and operational complexity.

Own AI Investing product areas across financial services. Define user problems, product direction, scope, metrics, roadmaps, and launches; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial products; monitor performance; and iterate using data, research, feedback, and production insights while balancing speed, usability, impact, compliance, and operational complexity.

Own AI Investing product areas across financial services, defining user problems, product direction, scope, metrics, roadmaps, and launch plans. Partner with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Launch features, monitor performance, use research and feedback to guide iterations, and balance speed, user experience, business impact, compliance, and operational complexity.