Top Machine Learning Engineer Jobs in San Francisco, CA

Lead the design, development, and deployment of machine learning models, collaborating with teams and mentoring engineers. Focus on scalable ML workflows.

The Principal ML Engineer at Agero will develop and productionize a Dispatch System using ML models, optimize decision-making processes, and lead a team to improve operational performance.

As a Principal Machine Learning Engineer, you will develop multimodal AI experiences, design agent interactions, and lead cross-team initiatives while ensuring AI safety and reliability.

As an Applied Scientist, you will design and implement machine learning models, develop personalized systems, and enhance decision-making through AI technology to improve user experience and business operations.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

The Senior Machine Learning Engineer will design and implement ML systems, optimize data pipelines, and collaborate on ML workflows for personal injury legal solutions.

Own the full ML lifecycle for ads bidding stack, developing models for auction optimization and collaborating with a team to enhance platform effectiveness.

As a Staff ML Research Engineer, you will develop and optimize ML algorithms for drug discovery, transitioning high-impact prototypes into robust products and managing software development across the lifecycle.

Develop and optimize machine learning systems for Yahoo News, collaborate with teams to enhance user experience and editorial tools.

Lead the design and implementation of advanced ML systems at Airbnb, mentoring engineers and shaping concepts into impactful products.

Lead the creation and optimization of machine learning algorithms, develop and refine production-grade models, and drive testing of innovative algorithms using historical data.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

As a Machine Learning Engineer, you will perform analysis on healthcare data, develop and deploy clinical machine learning models, and collaborate with various stakeholders.

Design, develop, and deliver machine learning models for clinical data. Collaborate with stakeholders and optimize production ML systems.

As an Applied AI Engineer at Luminai, you will design experiments, optimize machine learning models, and enhance AI platforms for healthcare automation.

Lead the development and implementation of machine learning solutions, managing a team to drive strategic decisions and innovative business outcomes.

As a Senior ML Engineer, you'll design, develop, and deploy ML models for product features, collaborate with teams, and drive research initiatives.

The Senior Applied AI/ML Scientist will lead the design and deployment of AI solutions, collaborate on impactful features, and enhance product capabilities by leveraging advanced AI and ML techniques.

The Machine Learning Engineer develops production ML algorithms and recommendation systems, collaborates with teams, and optimizes user experiences.

As a Senior Machine Learning Engineer, you will enhance diffusion models, conduct research, collaborate on system implementations, and communicate findings effectively.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

Develop and improve machine learning models for Pinterest's various product surfaces, utilizing deep learning and advanced data processing.

Develop and execute ML technology stack vision for Ads, improve ML models, and enhance content understanding using LLMs in a collaborative environment.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

Design, implement, and deploy machine learning models and systems for recommendations and related problems. Collaborate with engineers, data scientists, and product partners to analyze data, build proofs-of-concept, develop ML/optimization models, write production-quality code, and evaluate models against business goals.