Top Tech Jobs & Startup Jobs in Los Angeles, CA

Research, design, and train foundation models for robotics; align text-based reasoning with low-level control policies; evaluate zero-shot generalization; run experiments; integrate models into robotic systems and present findings externally.

Lead product strategy and roadmap for AI and robotics products, translating VLA and agentic RAG breakthroughs into customer value, defining safety/usability/performance metrics, working with enterprise adopters, and driving cross-functional delivery.

Lead developer relations and growth for a decentralized AI agents platform: create technical docs, tutorials, and code samples; represent the project at global events; engage and support developers across Discord/Telegram/GitHub; identify onboarding friction and collaborate with product and partner projects to drive adoption.

Run adversarial tests on language and multimodal models, build guardrails and real-time filters for autonomous tool use, and support RLHF alignment and constitutional AI development to ensure safe AI deployment.

Lead end-to-end technology for a greenfield, white-label consumer engagement and rewards platform. Define architecture, build scalable backend and infra for real-time events, points/wallet systems and tokenised rewards, oversee web and mobile products, integrate external systems, ensure production readiness and security, and hire and scale the engineering organisation while transitioning from hands-on delivery to strategic leadership.

Drive institutional adoption of the platform by sourcing and managing Tier-1/2 institutional prospects, negotiating partnerships and integrations, coordinating onboarding/compliance, advocating product needs, and representing the firm at global summits.

Design and architect multi-agent orchestration frameworks, build tool-calling pipelines and reasoning loops, and optimize latency and token usage for real-time agentic workflows and autonomous operations.

Optimize, compress, and distill large language and vision models for on-device inference. Build pipelines for distillation and hardware-specific compilation, and benchmark performance across NPU/GPU architectures.