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The Staff Machine Learning Engineer will enhance batch inference services and tooling for financial crime detection, work on infrastructure for model development, and lead AI/ML initiatives within Cash App. Responsibilities include collaborating with various teams, developing prototypes, and driving strategic roadmaps.
As a Data Science Manager, you will lead a team to develop innovative credit and lending models, enhance financial inclusion, and improve risk assessment. You will drive cross-functional initiatives, manage advanced machine learning projects, and ensure compliance with legal standards while aligning with Chime’s business goals.
As an Application Engineer, you will oversee design and implementation of assigned products, manage risks, analyze and deploy new user stories, guide junior engineers, and enforce IT standards. Collaboration with various stakeholders is crucial for achieving team commitments and ensuring high reliability of solutions.
The Staff Machine Learning Engineer will architect and scale recommendation systems for the streaming app Max, collaborating with various teams to enhance core machine learning infrastructure and projects. The role emphasizes leadership in promoting experimentation, data-driven innovation, and mentoring engineers while ensuring high standards in technical work and project execution.
The Staff Machine Learning Engineer will lead the Conversational AI team at Square, focusing on designing and optimizing machine learning solutions across products. Responsibilities include driving ML projects from inception to production, collaborating with various stakeholders, and providing mentorship to team members.
The Senior Machine Learning Engineer will design and manage distributed services and tools for Personalization Machine Learning at Cash App, focusing on recommendation and ranking systems. The role involves leading cross-functional projects, ensuring code quality, and mentoring fellow engineers, while collaborating with various teams to implement machine learning solutions.
The Senior Machine Learning Engineer will design and implement machine learning systems to combat fraud in Cash App's banking products. This role involves developing ML pipelines, collaborating with teams to enhance machine learning practices, and advancing the platform to support robust, scalable solutions for end-users.
As a Senior Machine Learning Engineer at TrueML, you'll architect and implement ML infrastructure, develop production-grade ML pipelines, and maintain systems for real-time and batch decision-making. You'll collaborate with data engineers and data scientists to scale algorithms and ensure robust deployment of machine learning models.
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As a Principal Engineer in ML/AI, you will lead technical efforts across teams, drive product development, set engineering standards, and provide mentorship while collaborating closely with various stakeholders to enhance and innovate financial services.
The Threat Analyst will analyze malware and detection tickets, focusing on improving detection capabilities through proactive analysis. Responsibilities include working with internal partners to resolve inquiries on malicious activity detections and providing insights for data science regarding detection efficacy.
The Applied AI/ML Senior Associate will develop machine learning models for tasks like NLP and recommendation systems, collaborate with cross-functional teams, and analyze model performance. The role requires independent learning and innovative thinking in machine learning.
The Senior Machine Learning Engineer will design and build services for ML modelers, integrate data streams to create efficient models, and lead MLOps initiatives. The role involves collaborating with various teams to enhance ML tools and infrastructure while maintaining production software and developing new solutions.
As a Senior Machine Learning Engineering Manager, you will lead the end-to-end machine learning lifecycle, from data collection to deployment. You'll implement novel techniques, mentor team members, and collaborate with cross-functional teams to ensure effective communication and innovation.
The Senior Machine Learning Engineer will focus on utilizing machine learning technologies to develop risk-based solutions that enhance customer verification processes and reduce fraudulent identities. Responsibilities include designing ML pipelines, maintaining model platforms, and shaping long-term ML strategies while collaborating with various teams at Cash App.
As part of the Sponsored Advertising team at Chewy, you will lead machine learning initiatives to enhance product search and ad relevance, collaborating with product leaders to develop and deploy models that improve user engagement and vendor visibility. Responsibilities include building predictive models and sharing insights with leadership.
As a Machine Learning Engineering Manager, you will lead a team to implement MLOps practices, manage machine learning projects, mentor engineers, and oversee the development of ML pipelines. Collaboration with Data Science and Data Architecture teams is crucial to drive innovation and ensure best practices in machine learning.
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.
As a Senior Applied Scientist at Chewy, you will lead the deployment of machine learning and data science to enhance shopping experiences, develop new models, and influence product and engineering strategies. You will mentor junior scientists and present research findings to business leaders.
Senior Product Associate in Machine Learning and AI role focused on developing innovative solutions using AI, machine learning, and a design-thinking approach to enhance customer and employee experiences. Responsibilities include new product opportunities identification, user research, product metrics analysis, and collaboration with cross-functional teams.
As a Lead Machine Learning Engineer at Capital One, you will design and implement machine learning applications, focusing on high availability and performance. You will collaborate with various teams, develop optimized ML models, automate tests, and ensure responsible AI practices. This includes maintaining and monitoring deployed models and utilizing cloud technologies for scalability.
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 Lead Machine Learning Engineer, you will innovate and implement AI and machine learning to enhance advertising processes, focusing on inventory forecasting, pricing, targeting, and ad delivery. You'll lead the architecture design of ad algorithms, develop scalable data analysis approaches, and mentor team members.
The Senior Machine Learning Engineer will innovate and enhance advertising solutions using AI and machine learning, focusing on ad inventory forecasting, pricing, and targeted advertising. This role involves algorithm architecture, scalable data analysis, and collaboration with various teams to optimize advertising processes.
The Lead Machine Learning Engineer will develop innovative AI and machine learning solutions for Disney's advertising platform, driving improvements in ad inventory forecasting, experience, pacing, pricing, targeting, and delivery. The role involves designing ad algorithms, conducting scalable data analysis, and collaborating across teams while mentoring junior members.
As a Principal Machine Learning Engineer, you will lead the development of prediction or optimization engines for advertising platforms, driving innovation through AI and machine learning. Responsibilities include designing ad algorithm architecture, developing scalable data analysis methods, and collaborating with cross-functional teams.
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