Top Tech Jobs & Startup Jobs in Los Angeles, CA

Design, build, and deploy production-grade ranking, embedding, and retrieval systems within customer environments. Engineer end-to-end ranking pipelines, data pipelines, low-latency model serving, monitoring, A/B testing, and continuous retraining. Provide white-glove deployment support, codify repeatable patterns, drive research in multi-stage retrieval and personalization, and uncover expansion opportunities.

Design, build, and scale low-latency distributed platform components; define technical vision and architecture; collaborate with product and ML teams; evaluate build-vs-buy decisions; prototype research breakthroughs and deliver robust, production-grade services.

Lead full-cycle enterprise sales into Fortune 500 retailers, marketplaces, and travel companies. Manage eight-figure deals with C-suite and technical buyers, coordinate internal resources, build procurement-ready ROI/business cases, run pilots/A-B tests, and drive land-and-expand growth while shaping GTM playbooks.

Lead end-to-end marketing for a category-defining AI enterprise platform: GTM strategy, demand generation, ABM, positioning, content, events, marketing ops, and team building to drive high-ACV pipeline and revenue influence.

Work as a technical partner to customers adopting Sequen AI, translating requirements into production-grade ML systems. Provide API integration support, systems architecture guidance, hands-on diagnostics, and stabilization from experiment to production. Advocate customer needs to product and engineering, identify usage patterns, drive long-term adoption and expansion, and manage stakeholder relationships across technical and business teams.

Design, build, and optimize production-grade Rust systems for low-latency model serving and real-time data ingestion. Implement high-throughput backend APIs, caching, and memory-efficient components. Debug distributed systems, establish benchmarking and monitoring, and collaborate with Applied Scientists to translate ML advances into scalable runtime systems.

Build and operate low-latency ML infrastructure for production ranking systems. Design model CI/CD, scalable inference pipelines, observability and evaluation loops, optimize serving performance, and partner with research to transition models to resilient production deployments.