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

The Solutions Architect for AI/ML at Snowflake will advise clients on best practices for Data Science workloads, design solutions, and build ML pipelines. Responsibilities also include working hands-on with SQL and Python, maintaining technical expertise and collaborating with teams to improve products.

The Applied AI Software Engineer will evaluate LLM-based agents, manage benchmarking, and ensure performance, safety, and reliability in healthcare settings. Responsibilities include designing evaluation plans, running experiments, collaborating with teams, and developing internal tooling for AI features.

Drive and implement machine learning applications, optimize practices, formulate hypotheses, and communicate requirements to enhance advertising strategies and systems.

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

The Senior ML Backend Engineer will design and maintain backend services, integrate ML models, and ensure compliance and performance within healthcare workflows, while leading technical initiatives and mentoring team members.

As a Machine Learning Engineer, you'll design and implement predictive analytics systems, optimize modeling processes, and maintain production systems while collaborating with teams.

The Machine Learning Engineer will scale core infrastructure, manage data pipelines and model evaluation, and improve benchmarking systems. Collaborate with teams to enhance AI evaluation methodologies.

Lead a team to enhance ML-driven trading strategies, conduct market research, build production-quality code, and optimize strategy implementation in a quantitative trading environment.

Research Engineer will conduct Machine Learning research to enhance localization and global entertainment, focusing on ASR, Speaker Diarization, and Audio Understanding.

The engineer will develop and optimize AI algorithms, enhance frameworks, tackle training challenges, and improve model performance while collaborating across teams.

As a Senior Machine Learning Engineer, you'll develop perception modules for autonomous vehicles, focusing on scalability and adaptability across global environments. Responsibilities include collaborating on algorithms, conducting large-scale experiments, and end-to-end deployment of models.

The role involves designing and implementing post-training algorithms for LLMs and DLMs, improving training pipelines, collaborating with researchers, and demonstrating engineering practices.