inference jobs in San Diego

Senior engineer responsible for designing, building, and optimizing large-scale AI platforms for wireless, 5G, and connected devices. You will architect end-to-end AI/ML pipelines, integrate models into chipsets and cloud/edge environments, and deliver scalable inference services, tools, and SDKs.…See more Key responsibilities include model deployment, performance tuning on heterogeneous hardware, MLOps automation, and monitoring across silicon, software, and product teams.

As a Staff Machine Learning Engineer focused on model optimization, you will create and implement ML techniques, frameworks, and tools enabling efficient discovery and deployment of state-of-the-art ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized inference/training software and compiler tools, and collaborate with cross-functional teams on joint hardware-software design.…See more The role requires 4+ years of hardware/software/systems engineering experience (or equivalent with advanced degree), deep expertise in ML frameworks (TensorFlow, PyTorch, Keras, Caffe), embedded systems optimization, and programming languages like Python or C++. You will work independently with minimal supervision, provide technical guidance to team members, and influence key organizational decisions through consultation with senior leadership.

As an LLM Engineer at Qualcomm, you will create and implement machine learning techniques, frameworks, and tools for efficient discovery and deployment of ML solutions across mobile, edge, auto, and IoT products. You will model, architect, and develop advanced ML hardware co-designed with software, develop optimized software for AI model deployment (kernels, compilers, model efficiency tools), and lead ML technique application into products.…See more You will work independently with minimal supervision while providing technical guidance to team members and collaborating across cross-functional teams on joint hardware-software design.

As a Machine Learning Engineer at Qualcomm, you will develop and optimize machine learning frameworks, tools, and algorithms for deployment across mobile, edge, automotive, and IoT products. You will collaborate with cross-functional teams to design hardware-software co-optimized solutions, build efficient inference and training systems, and create ML kernels and compiler tools.…See more The role requires proficiency in ML frameworks (TensorFlow, PyTorch, Keras), embedded systems optimization, and programming languages like Python or C++, with experience in problem domains such as NLP or multimedia.

Lead machine learning strategy and development for AppFolio's Leasing products, owning the ML roadmap and autonomous leasing agent architecture. Build evaluation frameworks, model quality infrastructure, and establish ML standards across the Leasing Engineering team while ensuring production-grade reliability, SLOs, and observability.…See more Translate research into shipped features by evaluating fine-tuning approaches, RAG patterns, and agentic systems; operate with production discipline on a SaaS platform serving real customer workflows.

Lead Qualcomm's next-generation AI accelerator platform as senior engineering director, defining software vision, architecture, and roadmap while managing multiple engineering organizations spanning system software, device drivers, AI runtimes, compilers, ML frameworks, and platform SDKs. Partner with hardware teams on co-design, drive software readiness across chip development milestones, and establish performance/power/reliability goals.…See more Requires 9+ years software engineering experience (or PhD + 8 years), 4+ years with C/C++/Java/Python, and demonstrated expertise in AI/ML stacks, compiler technologies, runtime systems, or high-performance computing.

Senior Engineer, Machine Learning at Element Biosciences will design, develop, and optimize deep learning models (CNNs, Vision Transformers, U-Net) for biological image analysis and deploy them to production on AWS or imaging instruments. Responsibilities include building end-to-end ML pipelines from data ingestion through inference, applying advanced image processing and computer vision techniques to multimodal biological images, and analyzing single-cell and multiomic data.…See more The role requires 5–7 years of experience with a Master's degree (or 0–3 years with a PhD) and hands-on proficiency in PyTorch, Python, and cloud deployment, with strong preference for experience in biomedical image modalities.