Top Tech Jobs & Startup Jobs

Build and operate scalable backend systems supporting AI-powered features. Design inference pipelines, orchestration workflows, and ML model service boundaries while optimizing latency, throughput, caching, batching, and streaming. Own observability, system health, alerting, and incident response for high-scale distributed services. Collaborate with client and machine learning engineers to deliver reliable APIs for mobile and desktop applications.

Build and maintain production-grade native iOS applications using Swift and SwiftUI, integrating AI capabilities through backend APIs and on-device machine learning. Design resilient real-time user experiences, optimize performance and battery usage, collect telemetry, collaborate with ML and backend teams, and maintain high App Store quality standards.

Build and operate scalable AI backend systems, including inference pipelines, orchestration workflows, distributed microservices, and production APIs. Own observability, system health, alerting, and incident response while optimizing latency, throughput, reliability, and cost through caching, batching, and response streaming. Collaborate with client and machine learning engineers to deliver efficient AI features across mobile and desktop platforms.

Build and maintain production-grade native iOS applications using Swift and SwiftUI. Integrate AI and machine learning features through backend APIs, design resilient real-time interaction patterns, optimize performance and memory usage, collect telemetry, and collaborate with ML and backend teams on architecture and API contracts. Ship and support reliable consumer-facing applications in the App Store.

Design, build, deploy, and optimize production-grade machine learning systems for a proactive AI platform. Own projects end to end across data curation, model training, evaluation, inference, monitoring, and iteration. Translate research into reliable systems, troubleshoot production anomalies, balance latency and cost at scale, collaborate cross-functionally, mentor engineers, and uphold high standards for robust architecture, safety, and technical execution.

Design, build, deploy, and optimize production-grade machine learning systems for a proactive AI platform. Own projects end to end, including data curation, model training, evaluation, inference, monitoring, and iteration. Translate research into reliable systems, troubleshoot production issues, optimize latency and cost, collaborate with research, engineering, and product teams, and mentor other engineers.

Design, build, deploy, and optimize production-grade machine learning systems for a proactive AI platform. Own projects end to end, including data curation, training, evaluation, inference, monitoring, troubleshooting, and iteration. Translate research into reliable systems, balance latency, cost, safety, and scale, and collaborate with research, engineering, and product teams. Mentor engineers and uphold strong standards for code quality, architecture, and technical judgment.

Design, build, deploy, and maintain production-grade machine learning systems for a proactive AI platform. Own projects end to end across data curation, model training, evaluation, inference, monitoring, and optimization. Translate research into reliable systems, troubleshoot live production issues, improve performance iteratively, and balance latency, cost, safety, and reliability. Collaborate with research, engineering, and product teams while mentoring engineers and conducting technical reviews.

Design, build, deploy, and optimize production-grade machine learning systems for a proactive AI platform. Own projects end to end across data curation, model training, evaluation, inference, monitoring, and iteration. Troubleshoot live model and system issues, balance latency, cost, reliability, and safety, and collaborate with research, engineering, and product teams. Mentor engineers, conduct code reviews, and independently drive complex initiatives from concept through launch.

Design, build, deploy, and own production-grade machine learning systems for a proactive AI platform. Responsibilities span data curation, model training, evaluation, inference, monitoring, troubleshooting, optimization, and continuous iteration at scale. The role translates research into reliable products, balances latency, cost, safety, and performance, and collaborates with research, engineering, and product teams. It also includes mentoring engineers, conducting code reviews, and independently driving complex initiatives from concept through launch.