Top Senior Level Machine Learning Jobs in San Francisco, CA

As a Senior Staff Machine Learning Engineer at Liftoff, you will own and develop ML models with direct business impact, mentor team members, stay updated on latest ML research, and influence team roadmaps. Requires 10+ years of ML experience, deep neural network expertise, strong coding skills, and a degree in Machine Learning, Math, Physics or similar.

Build, optimize, and deploy machine learning models for identity resolution and ads attribution. Collaborate with cross-functional teams and stay up-to-date with the latest technology. Strong understanding of machine learning approaches and algorithms.

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.

As a Senior Principle Machine Learning Engineer at Atlassian, you will integrate cutting-edge AI capabilities into Atlassian products, extract knowledge and insights from data, and transform the way teams collaborate. You will craft and implement machine learning models, analyze large datasets, design robust models, collaborate with cross-functional teams, and drive AI adoption. Compensation for this role ranges from $198,400 to $318,600 per year.

As a Distinguished Engineer at Capital One, you will lead large-scale machine learning initiatives to solve challenging business problems in the financial services industry. You will provide technical leadership, design and implement machine learning applications, optimize data pipelines, and mentor engineering teams. The role requires at least 10 years of experience in data-intensive solutions using distributed computing, proficiency in Python, Scala, C, C++, and expertise in machine learning development lifecycle.

The Software Engineer, Machine Learning will collaborate across machine learning, platform, and product engineering teams to develop scalable solutions using data and machine learning engineering. Responsibilities include training models, contributing to various serving stacks, building ML infrastructure, developing communication devices, and advancing technical approaches to scalable machine learning.

Lead Machine Learning Engineer role at Grammarly, responsible for building scalable ML solutions for marketing problems, driving business impact, and collaborating with cross-functional teams.