Top Remote Machine Learning Jobs in San Francisco Bay Area, CA

Lead a team to advance performance marketing through machine learning and data-driven strategies, optimizing budget allocation and measuring impact.

Design and implement scalable data pipelines and ML algorithms to optimize StackAdapt's digital advertising platform. Collaborate with teams to solve complex problems.

As an AI/ML Engineer, you will design and deploy models for real-world applications, optimize data pipelines, and engage with global leaders to enhance AI technology's impact across sectors like healthcare and government.

The AI/ML Software Engineer will design, implement, and maintain AI features and ML models for Rocket Lawyer's platform, working closely with cross-functional teams.

The role involves building end-to-end modeling pipelines, developing models, delivering insights to stakeholders, and collaborating with a technical team in a fast-paced environment.

As an Applied Machine Learning Scientist, you will innovate and develop machine learning algorithms, write production code, and collaborate to implement and test these solutions based on historical data.

Lead design, development, and production deployment of ML and algorithmic solutions. Own end-to-end ML systems, support distributed production reliability, communicate tradeoffs, and apply generative AI, LLM fine-tuning, RAG, and agentic techniques to product problems.

The role involves building AI technologies for customer service, developing ML systems, and collaborating with cross-functional teams to enhance user experiences.

The Senior Machine Learning Engineer will design, prototype, build AI systems, evaluate ML models, and improve Vectara's AI Agents with a focus on reliability and performance.

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

The Senior Machine Learning Engineer will develop core ML models, manage data pipelines, and collaborate with stakeholders to deliver scalable ML solutions.

The role involves developing and deploying ML solutions, focusing on LLMs and deep learning, while ensuring alignment with business objectives and tech best practices.

As a Machine Learning Engineer/Scientist, you will develop ML systems for cryopreservation research, manage data pipelines, and deploy models for scientific insight.

The ML Research Engineer will develop training pipelines for atomistic simulation models and collaborate with researchers to optimize training workflows.

Collaborate to scale self-driving systems, build training frameworks, profile model performance, and evaluate emerging technologies for training and inference.

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

The Principal Software Engineer II will build and maintain machine learning components in Elasticsearch, collaborating with teams, writing scalable code, and owning projects from design to implementation.

As a Senior Machine Learning Engineer, you will design and implement systems for ML and NLP, optimizing models and tools for Clover's healthcare solutions.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

Contribute to developing machine learning models for multi-scale biology, focusing on design, deployment and optimization across teams and technologies.

As a Senior AI/ML Engineer, you will design and develop advanced AI solutions for finance, focusing on ML and GenAI, ensuring compliance and operational efficiency.

Design and implement machine learning models to solve business problems, analyze data for insights, and optimize model performance.

Lead the Performance ML squad, managing and mentoring engineers while driving the development, deployment, and strategy of predictive models for advertising.

Manage and mentor a team of machine learning and data engineers, overseeing ML model development, data pipelines, and collaborating with product teams on technical requirements.

The AI/Machine Learning Specialist designs and implements AI solutions, collaborates with cross-functional teams, and continuously improves ML processes.