Top Machine Learning Jobs in San Luis Obispo, CA

Design and maintain datasets, build and evaluate domain-specific ML and vision-language models for real-time privileged access threat detection; deploy and optimize Python/Docker inference services integrated with WebSocket/WebRTC and protocol-level interfaces; monitor and document production models.

The Staff ML/AI Platform Engineer will design, prototype and deploy AI/ML models, optimize pipelines, mentor junior engineers, and collaborate closely with other teams to develop machine learning solutions.

The Director of AI & ML is responsible for establishing and leading the AI function, defining AI strategy, building a high-performing team, and delivering production-grade ML and AI solutions within healthcare payer workflows.

Responsible for designing, building, and operating AI-powered features, scalable APIs, and maintaining integrations within ClickHouse's AI/ML ecosystem.

Seeking a Principal AI/ML Researcher and Engineer to lead research and development in Bayesian Learning and Reinforcement Learning. This role involves architecting large-scale AI systems, model development, and driving technical strategy for innovative AI platforms that enhance personalization and decision-making at Airbnb.

Responsible for fine-tuning state-of-the-art LLMs, optimizing models for deployment, and driving AI architectural decisions. Collaborate with cross-functional teams to develop impactful AI products.

As an MLOps/ML Platform Engineer, you will build and manage ML systems, optimize workloads, and ensure production model reliability while collaborating across teams.

As a Senior Machine Learning Engineer, you will develop and deploy ML models for health data analysis, collaborating with cross-functional teams to ensure reliability and regulatory compliance.

Design and implement ML infrastructure for scalable deployment, collaborate across teams, optimize ML systems, and enhance tooling.

As an Applied Machine Learning Platform Engineer, you'll design and maintain training infrastructure, manage distributed pipelines, and optimize data workflows for machine learning models.

As a Senior Machine Learning Engineer, you'll design and develop infrastructure and models for AI-powered applications while collaborating with teams to enhance product functionality.

The VP of Research, Machine Learning will set research direction for AI systems, focusing on context representation, reasoning, and evaluation frameworks while ensuring product safety and alignment.

Responsible for building and maintaining end-to-end ML pipelines and deploying production-grade ML systems. Tasks include model fine-tuning, evaluation, and collaboration with engineering teams.

Lead computer vision projects and develop ML models for power grid analysis while mentoring engineers and ensuring software quality standards.

The AI Engineer will build data pipelines and improve ML systems for reliability in production. Responsibilities include schema design, data infrastructure, and model evaluation, ensuring high-quality outputs and integration with product workflows.

The AI Director will oversee ML bot development and implementation, identify AI opportunities, educate teams, and prototype AI solutions.