Top Machine Learning Jobs in San Francisco Bay Area
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As an Applied Machine Learning engineer at Atlassian, you will work on the development and implementation of cutting-edge machine learning algorithms, training models, and collaborating with product, engineering, and analytics teams to integrate AI functionalities into Atlassian products. Responsibilities include designing system and model architectures, conducting model evaluations, and applying AI/ML to improve Atlassian products.
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.
Design equitable and competitive compensation programs. Base pay ranges from $165,500 to $265,800. Additional benefits such as bonuses, commissions, and equity may be provided.
This is a senior-level machine learning engineer role focused on modeling for underwriting and credit. The role involves building and integrating ML solutions for evaluating customer cash flow risk and optimizing automated decisioning using AI/ML techniques. The engineer will work cross-functionally with finance, product, and engineering teams to bring solutions into production.
Design, build, and manage distributed services and pipelines for underwriting and credit at Cash App. Lead cross-functional projects, maintain code quality, collaborate with teams, and contribute to the growth of development capabilities through mentoring.
The Senior Machine Learning Engineer II at Cruise is responsible for researching, developing, and optimizing machine learning algorithms for self-driving vehicles. The role involves being a technical leader, guiding technology choices, balancing tradeoffs, and enabling team members through effective design and code.
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Develop advanced algorithms, execute statistical and data mining techniques, evaluate emerging datasets, contribute to thought leadership, possess strong communication and critical thinking skills.
The Machine Learning Engineer at ZS will be responsible for building, orchestrating, and monitoring model pipelines, scaling machine learning algorithms, enhancing ML engineering platforms, implementing ML Ops, writing production-ready code, collaborating with client teams, and researching and evaluating new technologies.
Designing and managing distributed services and pipelines for Underwriting & Credit at Cash App. Leading cross-functional projects, ensuring high code quality, collaborating with different teams, and mentoring engineers. Solving technical problems at scale and contributing to development capabilities.
Senior Machine Learning Engineer role at Roblox focusing on leveraging Generative AI for 3D content creation. Responsibilities include developing ML models, mentoring team members, staying updated with latest research, and publishing innovations. Requires 3+ years of ML experience, expertise in Python and deep learning frameworks, and familiarity with generative AI techniques.
Samsara is looking for an experienced Machine Learning Engineer for our Machine Learning Engineering team. Our Machine Learning team is responsible for leading the teams that build and ship Samsara’s AI features, and the infrastructure that supports them. This includes computer vision, large language models, and multimodal machine learning on edge devices and in the cloud to support our rapidly growing footprint of customers. This organization is building the ML foundation to stay ahead of the needs of our expanding customer base and platform.
As a Principal Data Scientist at Capital One's Emerging ML team, you will work on developing machine learning models, conducting research on self supervised learning and transformer models, and analyzing customer behavioral data to improve financial experiences.
Research and build high-impact end-to-end machine learning systems for customer growth, drive the design of scalable ML solutions in production, mentor engineers and data scientists, contribute back to research community
Build AI and Machine Learning solutions to transform user experience and workflow efficiency of enterprise services. Collaborate with a team to produce quality software and work on data acquisition and evaluation metrics for performance and quality at scale. Drive innovation in AI technologies for future work experiences.
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