Top Remote Senior Level Machine Learning Jobs in San Francisco Bay Area

Lead a team of Machine Learning Engineers in developing ML solutions across marketing, product, and operations. Collaborate with cross-functional teams to build machine-learning based systems and guide strategic decisions in machine learning and data use.

Develop and improve machine learning models for customer support experiences, utilizing state-of-the-art algorithms and large language models. Collaborate with cross-functional teams to meet business needs and monitor model performance for continuous improvement.

As a Senior Software Engineer in the Central AI team at Atlassian, you will build and maintain core infrastructure for machine learning engineers and data scientists. You will lead projects, collaborate with teams, and tackle complex challenges. The role requires 5+ years of experience and fluency in Java, Kotlin, and Python.

As a Senior Engineering Manager of Machine Learning at Dropbox, you will lead a team of engineers to build and scale Dash, one of Dropbox's AI offerings. Your responsibilities include driving product monetization, fostering a collaborative culture, providing strategic direction, and contributing to technical and product strategies. The ideal candidate has a strong background in software engineering, distributed systems, and backend infrastructure, as well as experience in machine learning. This is a senior-level position requiring 7+ years of software engineering experience and at least 3+ years in direct management roles.

The Staff Machine Learning Scientist will be responsible for developing generative AI applications for healthcare, collaborating with cross-functional teams, conducting healthcare-focused research, and designing and implementing generative AI models for healthcare scenarios.

Seeking an ML Engineer specializing in constructing and managing robust, scalable, and high-performance compute platforms tailored for ML workflows. Responsibilities include designing core platform backend software components, working on large-scale initiatives, and participating in open source projects.

Designs, develops, and programs methods and systems to analyze big data sources and generate insights and solutions. Interacts with teams to identify data analysis questions and issues. Cleanses and integrates large datasets from multiple sources. Identifies meaningful insights and communicates findings to managers.