latency-optimization jobs in San Diego

As an Autonomy Engineer focused on VLA (Vision-Language-Action) pre-training, you will train capable robotic policies using deep learning, including pre-training base models on multi-embodiment trajectory data, fine-tuning for specific tasks, and optimizing for real-time edge inference. You'll own the full loop from data collection and curation through deployment, partnering with data and MLOps teams to build continuous training pipelines that ingest synthetic data and teleop logs.…See more The role requires 3+ years building production deep-learning systems with hands-on experience in LLMs, VLMs, or generative models, plus strong Python and PyTorch/JAX skills to profile, debug, and write maintainable research code.

Principal System Lead responsible for translating AI-driven use cases into scalable, power-efficient implementations on Qualcomm's mobile SoCs. The role spans the full AI stack—generative AI, diffusion models, on-device inference, and camera-centric workloads—requiring deep knowledge of AI software frameworks and optimization across performance, latency, memory, and power constraints.…See more You will define system-level architectural enhancements for AI accelerators, CPUs, GPUs, and memory subsystems, working across hardware, software, and platform teams to align designs with OEM product roadmaps. The position demands 8+ years of semiconductor product development experience, 5+ years in technical leadership, and strong ability to solve complex AI system challenges through quantitative analysis and cross-functional collaboration.

This role combines prompt engineering expertise with AI system governance and enterprise adoption strategy. The engineer will optimize LLM performance across platforms (OpenAI, Anthropic), design and configure AI agents and chatbots with knowledge grounding, and establish prompt governance frameworks and best practices.…See more Success requires 5+ years in AI/ML systems, 2+ years of hands-on prompt engineering, and demonstrated ability to evaluate AI performance, manage knowledge systems, and guide enterprise clients through AI tool adoption and deployment.

Own end-to-end feature development for Voice AI on Windows, including wake-on-voice, ASR, translation, transcription, and TTS. Design and implement Windows audio and driver stack solutions leveraging Qualcomm SoC capabilities while meeting strict latency and power targets.…See more Build components across user-mode and kernel-mode boundaries using UMDF/KMDF, integrating with Windows audio frameworks. Optimize performance and debug complex multi-threaded issues across hardware/software boundaries.

Lead Arm's SoC interconnect technology team as a senior architect with 15+ years of experience designing large-scale SoCs. Own performance modeling, microarchitecture, RTL design, and verification strategy for interconnect IP; drive adoption of industry standards (AMBA AXI/ACE/CHI, etc.) across CPU, GPU, NPU, and memory subsystems.…See more Mentor a team of architects and engineers while leading complex projects to tape-out, with expertise in coherent protocols, cache coherency, latency/bandwidth/power optimization, and system-level debug.

Staff engineer leading architecture and evolution of Qualcomm's Ambient Perception Platform for always-on, context-aware AI on power-constrained edge devices. Responsibilities include designing low-power AI runtime platforms, multimodal sensing systems, secure data architectures, and heterogeneous computing frameworks across Android, Linux, Windows, XR, automotive, and IoT.…See more Requires 4+ years software engineering experience (or equivalent with advanced degree), 2+ years with C, C++, Java, or Python, and expertise in embedded systems, ARM/DSP/NPU optimization, and edge AI workload efficiency. Strong preference for 8–12+ years in software architecture, platform frameworks, and heterogeneous SoC development.