Top Machine Learning Jobs in San Luis Obispo, CA

As a Sr. Machine Learning Engineer, you will develop and deploy ML models, enhance care personalization, and mentor teams while optimizing workflows.

Seeking a build engineer with strong software engineering skills to manage CI/CD systems and establish best practices for large-scale monorepos for ML applications.

Build a next-generation ML data and feature infrastructure platform to enhance the productivity of ML practitioners and improve feature accessibility.

Join Netflix's Algorithms team as a Machine Learning Software Engineer to design and develop solutions for personalization systems. Collaborate on scalable machine learning algorithms and enhance software engineering practices.

As an ML Engineer, you will build and productionize predictive models for ad inventory and campaign performance, contributing to the growth of Netflix's ad platform.

Develop and deploy machine learning models for real-time ad systems, optimizing inventory management, targeting, and campaign effectiveness for Netflix's advertising platform.

Responsible for building scalable microservices and data pipelines, mentoring junior engineers, and ensuring data quality for ML training.

Lead a team of ML engineers and software engineers focused on Ads Content Understanding, driving innovation and efficiency in Ads Monetization.

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

As a Senior ML Ops Engineer, you'll automate, monitor, and scale machine learning workloads, manage infrastructure, and collaborate with teams to productionize AI services.

Lead the architecture and development of AI and ML features, design evaluation frameworks, and mentor team members to enhance ML-driven product experiences.

The Principal Product Manager will define and execute strategies for machine learning-driven search suggestions, working cross-functionally to enhance search experiences and align with business objectives.

Drive cross-team engineering efforts to improve user experience on Homefeed by implementing large-scale machine learning systems and enhancing data processing efficiency.

Design and optimize ML models for AI-powered facial analysis, focusing on computer vision and generative models, ensuring accuracy and efficiency in a B2B SaaS environment.

Seeking a senior product designer for AI/ML platform development, responsible for transforming user experiences, leading projects, and mentoring designers. Emphasis on design impact and collaboration with cross-functional teams.

As a Data Scientist/Machine Learning Engineer, you'll finetune models, improve data quality, add new signals, and push solutions to production.

As a Senior Applied Machine Learning Engineer at Upwork, you'll leverage advanced machine learning techniques to enhance search and recommendation systems, analyze data to improve user experience, and develop large language models.

Lead and grow a global engineering team, drive technical strategy, and deliver value through innovative solutions while fostering a culture of growth and collaboration.

The Senior Machine Learning Engineer will lead ML initiatives, design scalable systems for data processing, and mentor colleagues to build robust ML infrastructure.

The Senior Machine Learning Engineer will design and implement ML solutions, collaborate with teams, and contribute to scalable infrastructure enhancements.

This role involves deploying and optimizing machine learning models for autonomous vehicle motion planning, ensuring performance and reliability in production settings.

Lead the technical vision and architecture for machine learning and data systems, overseeing scalable infrastructure and collaboration across teams.

Develop, evaluate, and deploy AI systems and machine learning models, focusing on NLP and multimodal models. Collaborate with teams and publish research.

Lead the development and deployment of machine learning solutions that enhance content discovery on Netflix, partnering with engineering and creative teams.

Design, build, and maintain distributed training infrastructure for Ads ML models, while collaborating with ML engineers to optimize training processes.