vlm jobs in San Diego

As an Autonomy Engineer focused on VLA (Vision-Language-Action) pre-training, you will develop and train deep learning policies for humanoid robots, owning the full pipeline from data collection and curation to model deployment. You'll pre-train base models on diverse multi-embodiment trajectory corpora, fine-tune policies for specific tasks, work with MLOps teams to scale distributed training, and build continuous pipelines that ingest synthetic data and teleop logs.…See more This is primarily a deep learning role requiring 3+ years of experience shipping neural network models, hands-on expertise with LLMs, VLMs, or generative models, and strong proficiency in Python and PyTorch or JAX.

Lead the integration of autonomy software with platform software for autonomous systems, responsible for building glue layers, investigating cross-system failures, and supporting deployment to hardware. Develop and maintain test infrastructure, instrumentation, and documentation; work with Flight Operations to define test objectives and analyze integration failures.…See more Design reference integrations, deployment workflows, and tooling for edge devices, and contribute to Pilot training materials. Requires deep C++ expertise, Linux development, and experience building, testing, and debugging software for robotics, perception, planning, or autonomous systems.

Qualcomm seeks a Staff Product Data Manager for AI Platforms & Systems Solutions to define product strategy and drive cross-functional decision-making for edge AI/ML platforms, inference runtimes, and agentic frameworks. The role requires deep technical expertise in Windows-ecosystem AI platforms, LLM/VLM models (1B–150B range), edge AI APIs/SDKs, and AI middleware frameworks, combined with the ability to work independently, influence senior leadership, and manage complex multi-year initiatives across matrixed organizations.…See more Responsibilities include assessing feasibility, translating innovation into shippable solutions, negotiating partnerships, and authoring technical specifications—all with minimal supervision and significant organizational impact. The ideal candidate brings 10+ years in product management or technical roles, experience shipping AI platforms, familiarity with standards bodies, and strong communication skills to convey complex information to diverse audiences.

Qualcomm seeks an ML/computer vision engineer to develop and optimize AI-accelerated vision algorithms for edge devices (mobile, automotive, robotics, AR/VR). You will design algorithms for depth estimation, optical flow, video super-resolution, 3D reconstruction, and SLAM, then optimize deep learning models for resource-constrained SoCs.…See more The role spans algorithm research, model architecture design, performance profiling across memory/compute/power/bandwidth, and cross-functional collaboration with hardware and systems teams to ship production models for key customer segments.

Design and develop embedded and cloud edge software applications focused on AI/GenAI, multimedia, and computer vision SDKs and frameworks for IoT products including drones, cameras, and AI boxes. Collaborate with systems, hardware, and architecture teams to build high-performance, real-time embedded software solutions.…See more Lead GenAI LLM/VLM inference workflows, multi-stream AI pipelines, and multimedia frameworks across Android, Linux, and embedded systems. Requires 2+ years of software engineering experience with C/C++, Python, or Java, plus preferred expertise in PyTorch, TensorFlow, ONNX Runtime, LangChain, LlamaIndex, Android architecture, Linux system programming, and graphics/GPU pipelines.

Build and optimize scalable LLM inference platforms at Qualcomm's Cloud AI team, implementing advanced serving techniques like KV-cache management, speculative algorithms, and model optimization. Contribute to production serving frameworks (vLLM, SGLang, Triton, TGI) and work with customers on deployment solutions.…See more Collaborate with compiler, firmware, and platform teams to drive efficient serving through autoscaling, load balancing, and routing. Requires deep understanding of transformer architectures, strong PyTorch and Python skills, computer architecture knowledge, and hands-on experience profiling and optimizing deep learning workloads.

Senior Machine Learning Engineer responsible for architecting, designing, developing, and deploying on-device AI prototype software for edge computing applications. The role requires expert-level proficiency in C++ and Python, deep knowledge of ML frameworks like PyTorch, and hands-on experience with low-level system debugging, performance tuning, and native inference driver development.…See more You will work in a multi-disciplinary research team advancing generative AI technology for the edge, including model fine-tuning, hardware acceleration, model quantization, and edge inference. A strong theoretical background in deep learning combined with embedded software development experience and modern software engineering best practices is essential.