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

The role involves designing de novo frameworks for molecular engineering, collaborating across teams to optimize data-driven biological experiments and integrating ML models with experimental systems.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

As a Staff Machine Learning Engineer, you'll design and productionize ML models, collaborate with various teams, and mentor junior staff, impacting mental health care accessibility.

The Senior ML Systems Engineer will build and maintain the training framework for large-scale language models, focusing on distributed training and performance optimization.

The Staff Machine Learning Engineer will design and build scalable ML systems, mentor engineers, and drive AI strategy at SailPoint, focusing on AI-powered identity security solutions.

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

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

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.

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 Senior ML Engineer will develop and optimize machine learning solutions for audience intelligence, build production pipelines, and collaborate with cross-functional teams to enhance user engagement and revenue.

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.

Design and build machine learning models for Zillow's product features, optimize AI components, and mentor engineers within a cross-functional team.