Top Machine Learning Jobs in San Francisco, CA
The Principal Engineer will lead efforts in machine learning and AI, collaborating with teams to build impactful products, setting technical standards, and mentoring others. Responsibilities include hands-on development, technical leadership, and influencing hiring and coding practices.
As a Senior AI Engineer, you will design, implement, and maintain large-scale AI/ML pipelines, focusing on training and tuning deep learning models and evaluating large language models while working on data collection and feature engineering.
As a Machine Learning Engineer, you will design, implement, and maintain large-scale AI/ML pipelines, tune and evaluate models, and develop evaluation frameworks and metrics. Your role includes building and evaluating deep learning models and transformer-based models, working collaboratively within an AI engineering team.
The Senior Machine Learning Engineer at Cash App will design and enhance ML inference services, support ML model development, and collaborate with cross-functional teams to drive strategic initiatives in financial crime detection.
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As a Senior Machine Learning Engineer at Atlassian, you will develop and implement advanced machine learning algorithms, collaborate with various teams to enhance AI functionalities across products, and guide junior engineers. Your role includes designing architectures, conducting model evaluations, and ensuring effective AI integration throughout the organization.
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The Staff Machine Learning Engineer will lead projects within the Square Conversational AI team, focusing on building scalable machine learning solutions. Responsibilities include collaborating with business leaders, developing ML products, mentoring team members, and overseeing the entire ML lifecycle from data collection to production.
As a Senior Technical Sourcer for Machine Learning at Snap, you will be responsible for sourcing, screening, and engaging candidates for machine learning roles. You will work with recruiters and hiring managers to understand hiring needs, develop sourcing strategies, and enhance the candidate experience, all while managing data and hiring metrics.
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As a Machine Learning Engineer on the On-Device ML team, you will design and prototype new features, build and implement ML models, collaborate with product teams, and launch and monitor model deployments, all aimed at enhancing Grammarly's writing assistance capabilities on devices.
The Director of Data Science and Machine Learning will lead the Machine Learning, Data Science, and Product Analytics teams, drive data-powered insights for product performance, and collaborate across departments to optimize business growth. Responsibilities include team leadership, defining strategic vision, fostering collaboration, and overseeing the development of ML and DS models.
Lead the Model Engineering team to develop state-of-the-art ML runtime environments, ensuring high availability and low latency for ML model deployment. Collaborate with product stakeholders to create innovative scalable platform solutions while mentoring team members and fostering a culture of inclusion and collaboration.
As an Applied AI Scientist at ZS, you will develop advanced algorithms, execute statistical techniques on large datasets, evaluate emerging technologies, and contribute to the firm's thought leadership by researching and publishing on evolving topics.
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