Top Machine Learning Jobs
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.
The Lead Software Engineer will develop and enhance Disney's advertising machine learning platform, focusing on improving inventory forecasting, ad delivery, pricing, and targeting using AI. This role involves creating scalable solutions for data analysis and modeling while collaborating with researchers and balancing architectural considerations.
The Executive Director will architect advanced AI solutions, including generative AI and large language models, while collaborating with cross-functional teams. Responsibilities include designing optimized AI models, developing ethical AI practices, and mentoring a team. The role requires extensive experience in AI/ML within the financial services sector and a strong understanding of data leverage and regulatory standards.
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 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.
As a Senior Technical Sourcer for Snap's Machine Learning Recruiting Team, you'll identify, source, and screen candidates for machine learning roles. You'll work with recruiters and hiring managers, develop strategies for a robust candidate pipeline, use hiring metrics for efficiency, and provide a positive candidate experience.
As a Senior Product Associate, you'll manage the lifecycle of AI/ML products, ensuring smooth deployment and scalability. Responsibilities include leading product lifecycle activities, overseeing testing, developing project plans, and establishing standardized methods for the product lifecycle. You will also collaborate with stakeholders and communicate technical concepts effectively.
As a Machine Learning Engineering Manager, you will lead a team in developing models and systems for user understanding and ranking improvements. Responsibilities include defining architecture, ensuring quality and scalability, and collaborating closely with infrastructure and ranking teams. You will conduct design reviews and maintain high technical standards in a fast-paced environment.
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As a Machine Learning Engineering Manager, you'll lead development of models and evaluation for user and content understanding, enhance ranking models for ads and growth, and oversee the architecture of the embedding platform, ensuring quality and scalability. You'll mentor your team while collaborating with stakeholders and driving technical excellence through code reviews.
As a Software Engineer focusing on Machine Learning Infrastructure at Snap Inc, you will design and implement solutions to enhance the company's core products. Your role involves working on systems that support machine learning applications, collaborating closely with cross-functional teams to improve user experiences.
The Software Engineer will work on Machine Learning Infrastructure, focusing on building innovative solutions that enhance Snap's core products and support the development of augmented reality experiences.
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 Machine Learning Engineer, you'll analyze complex datasets, develop models and algorithms, manage ML Ops, and enhance customer products. You'll communicate insights to senior management, supervise data analysis, and promote effective cross-functional collaboration within the team.
The Machine Learning Engineering Manager will lead a team to develop algorithms for user and content understanding, drive infrastructure for machine learning, and collaborate with ranking teams to enhance ad and content relevance. Responsibilities include overseeing architecture, performing code reviews, and fostering team collaboration.
As a Manager of Machine Learning Engineering, you will lead a team to develop models and signals for user and content understanding. You will define system architecture, ensure quality and scalability, and collaborate on improving ranking models for ads and content. Your role involves mentoring team members and enhancing machine learning infrastructure.
The Senior Technical Sourcer will support the recruitment of machine learning professionals by sourcing and screening candidates, executing strategies for a robust talent pipeline, and collaborating with teams to fill priority roles. They will utilize hiring metrics and maintain a positive experience for candidates throughout the recruitment process.
Lead a team in developing and optimizing a personalized video recommendation engine. Define the architecture, drive iterations, conduct performance analysis, and mentor engineers. Facilitate collaboration across departments to improve system reliability and efficiency.
Lead a team of engineers in developing a personalized video recommendation engine. Define the architecture for scalability and performance, conduct A/B testing, and improve the recommendation system through technical reviews and team mentorship.
Lead the technical direction of the Ad Ranking team at Snap, focusing on advancing ML capabilities for ad optimization. Design and scale machine learning models, collaborate with cross-functional teams, and stay current with ML technologies to solve complex advertising-related problems.
As a Principal Machine Learning Engineer on the Ad Ranking team, you will drive the technical roadmap, design and implement machine learning models, collaborate with cross-functional teams, and advocate for best practices in availability, scalability, and operational excellence for ad optimization strategies.
As a Machine Learning Engineer at Snap Inc, you will develop models using LLMs for various applications, promote new features, evaluate technical decisions, conduct code reviews, and ensure high code quality while building scalable products.
The Lead Machine Learning Engineer will focus on developing and optimizing algorithms for Hulu's recommendation and personalization systems. Responsibilities include collaborating with product and data teams, maintaining existing models, and establishing best practices in algorithm development and deployment.
As a Senior Technical Director on Discovery at Roblox, you'll drive the technical vision and implementation of machine learning solutions for search and recommendation systems. You'll lead engineers, collaborate with teams, and balance technology research with practical applications, aiming to enhance user engagement and retention.
As a Lead Machine Learning Engineer, you will design, develop, and implement ML applications, manage model performance, and collaborate with Agile teams to solve business problems. The role involves maintaining production models, leveraging cloud technologies, and ensuring best practices in responsible AI.
As a Lead Machine Learning Engineer at Capital One, you'll design and implement machine learning applications, collaborate with cross-functional teams, and solve complex problems through coding and model validation. You'll ensure high performance and reliability of deployed models while leveraging cloud technologies and CI/CD practices.
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