Top Machine Learning Jobs

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.

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'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.

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.

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.

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 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.

As a Machine Learning Scientist focused on Speech AI and NLP, you will research and produce advanced machine learning models and applications, collaborate across the firm to develop impactful software solutions, and design scalable data processing pipelines for optimizing business results. You will prioritize innovative learning and knowledge sharing.

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.

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.