batching jobs in San Diego

Develop, optimize, and validate AI/ML solutions that leverage Qualcomm's AI inference accelerators for data center and hybrid applications. Design and implement GenAI and LLM applications, perform model benchmarking, optimize deployment strategies, and drive system-level architecture decisions.…See more Apply deep expertise in ML frameworks, system performance profiling, and parallel computing to ensure best-in-class inference performance, power efficiency, and scalability across heterogeneous hardware.

AppFolio is hiring a Staff Machine Learning Engineer to design, build, and operate their ML platform on AWS, supporting training, fine-tuning, inference, RAG, and cost optimization across the organization's AI initiatives. You'll partner with applied AI and research teams to productionize prototypes, maintain multi-provider LLM reliability (OpenAI, Google, Anthropic), and operate AI safety guardrails and authorization layers.…See more The role requires production-scale ML infrastructure experience on AWS (ECS, SageMaker, GPU fleets), deep knowledge of model serving and inference optimization, hands-on language model training, and demonstrated cost discipline across AI workloads.

Build production inference systems that turn ML research prototypes into deployed, performant components under strict latency, throughput, memory, and accuracy constraints. Own the full pipeline from model optimization through deployment: profile and tune tensor execution, write Rust/C++/CUDA where necessary, build evaluation machinery tied to product metrics, and maintain reproducible deployment contracts.…See more You'll collaborate with research teams to surface shipping risks early and translate algorithmic work into engineering reality with explicit performance budgets and regression gates.

Qualcomm AI Research seeks a Senior AI Research Quantization Engineer to develop algorithms for efficient generative AI, LLMs, and multimodal models optimized for on-device deployment. The role focuses on advanced quantization techniques, model compression, inference optimization (batching, KV caching, speculative decoding), and system prototyping using Python and PyTorch.…See more You will collaborate across hardware, software, and systems teams to enable state-of-the-art models to run on power- and memory-constrained devices including smartphones, autonomous vehicles, robotics, and IoT platforms. A Bachelor's degree plus 2+ years of related engineering experience (or Master's with 1+ year, or PhD) is required.