image-segmentation jobs in San Diego

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.

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.

Design and architect next-generation ML inference infrastructure for globally distributed, multi-tenant model serving with high availability, scalability, and cost efficiency. Lead the development of low-latency, high-throughput inference systems supporting computer vision and multimodal models (CNNs, segmentation, object detection) using Scala, Java, and Go.…See more Build large-scale distributed systems with reactive frameworks, integrate enterprise feature stores, and extend CI/CD pipelines (GitHub Prow, Pulumi) with automation and policy enforcement. Design advanced observability frameworks, optimize ML algorithms for performance, mentor engineers, and ensure MLOps and compliance standards (GDPR, SOC2) across the platform.