Top Machine Learning Engineer Jobs in San Francisco, CA

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

The Machine Learning Research Engineer role involves optimizing ML models, handling data acquisition, and ensuring production readiness using Python and cloud services.

Lead the design and deployment of ML systems while mentoring junior engineers. Collaborate with teams to ensure technical solutions align with business goals, conducting experiments to improve outcomes.

As a Machine Learning Engineer at Ello, you'll develop an AI tutor by owning end-to-end projects, collaborating with experts, and utilizing cutting-edge machine learning techniques to enhance children's education.

Design and implement ML models and systems for the Highlight AI desktop assistant, collaborating with cross-functional teams to integrate AI features into the product.

Design and build scalable machine learning systems, mentor ML engineers, and collaborate with internal teams to enhance the ML platform.

The Principal Machine Learning Engineer will lead the Content Relevance team in optimizing personalized video recommendation systems, advancing core ML capabilities, and collaborating on tech strategies. This role also involves mentoring, technical direction, and applying best practices for system performance.

The Senior Machine Learning Engineer will develop and maintain ML feature systems, drive architectural decisions, and mentor engineers while collaborating with cross-functional teams.

The Senior Machine Learning Engineer will design innovative machine learning models for drug discovery, leveraging large-scale single-cell datasets and collaborating with ML Scientists to develop optimized models.

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

Research and develop improvements to machine learning models, collaborate with research and product teams, and evaluate model performance.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

As a Machine Learning Intern, you will work on advanced AI solutions, collaborate with teams to design ML systems, and analyze data to enhance user experiences at Dropbox.

As a Founding AI Engineer, you will develop an AI-powered knowledge platform, focusing on backend systems, machine learning data pipelines, and optimizing tech stack for performance while participating in the entire product lifecycle.

Develop innovative machine learning algorithms for protein modeling and design, collaborating with experimental biologists and refining predictions.

Lead and mentor a team of machine learning engineers to develop AI-driven product features, ensure production quality, and align with strategic goals.

The Machine Learning Modeler will design and scale intelligent systems for data-driven decision-making, implementing ML pipelines, and collaborating with analytics teams for model production and insights.

The intern will develop, deploy, and operate machine learning models, driving research projects to solve real-world problems and collaborate with senior engineers on identifying use cases for ML on blockchain.

The role involves building machine learning models to detect risky activities, collaborating with cross-functional teams, and enhancing modeling capabilities. Candidates should have extensive experience in machine learning and strong analytical skills.

As a Machine Learning Engineer in the Notifications team, you'll design and implement ranking and recommendation systems using LLMs, develop experiments, and collaborate with research teams to improve notification relevance and user experience.

Manage a team of Machine Learning Engineers, architecting systems for content integrity, and ensuring effective model training and deployment.

The role involves designing and implementing reinforcement learning pipelines for AI systems, integrating organizational data, and collaborating with product teams to enhance AI functionalities.