Top Machine Learning Jobs

As a Machine Learning Engineer, you'll train, test, deploy, and maintain machine learning models to provide AI solutions for national security, collaborating with cross-functional teams to deliver innovative solutions.

As a Machine Learning Engineer, you will develop, deploy, and maintain ML models while collaborating on AI strategies for national security.

In this role, you will design and develop AI and machine learning models, maintain data pipelines, evaluate model performance, and collaborate with cross-functional teams to integrate AI capabilities into web-based applications.

The Head of Machine Learning will manage 9 ML engineers, coordinate projects, contribute to system architecture, and promote team growth. Responsibilities include strategic leadership, project management, and technical mentorship to align ML initiatives with business goals.

As a Senior Machine Learning Engineer, you'll build infrastructure for ML, develop deployment models, integrate LLMs, and support research teams while ensuring code quality.

As an ML Engineering Intern, you'll support the perception and learned-behavior teams, developing code for automation and working with real field data on projects involving model training, optimization, and simulation.

As a Lead Machine Learning Engineer, you will operationalize ML models, collaborate with teams, solve complex problems, optimize data pipelines, and implement best practices in ML deployment.

The Senior AI/ML Engineer will develop and improve analytical tools, approaches, and architecture for scalable AI and machine learning solutions, collaborating with engineers and data scientists on innovative projects.

The Machine Learning Scientist will build and integrate ML models, analyze data, design scalable pipelines, and ensure robust model testing.

As a Senior Machine Learning Engineer at PayPal, you will develop and optimize ML models, preprocess large datasets, and deploy solutions to enhance fraud detection capabilities while collaborating with cross-functional teams.

The Principal Analytics & ML Engineer will architect scalable analytics and ML solutions, build data models and pipelines, and mentor teams on best practices. Responsibilities include developing analytical models, collaborating across teams, and driving impactful analytics projects.

Lead the development and optimization of machine learning models, oversee data analysis, deploy solutions, and mentor junior staff while driving strategic vision for ML initiatives.

The Machine Learning Engineer will design, train, deploy, and maintain ML systems for automation, forecasting, and analytics in music and entertainment. Responsibilities include ML model development, MLOps tooling, and collaboration with other teams.

The Principal Machine Learning Engineer will design and implement AI/ML solutions for game development, collaborating with cross-disciplinary teams to enhance workflows and developer efficiency.

The Senior ML Engineer will develop AI solutions for healthcare data, collaborating with various teams, contributing to AI strategy, mentoring, and maintaining expertise in AI technologies.

The Lead Machine Learning Engineer will design and develop ML evaluation systems, translate research to production, and mentor engineers. They must engage with various teams and stay updated on ML advancements.

The role involves developing advanced machine learning algorithms, solving complex optimization problems using reinforcement learning techniques, and leading technical projects while optimizing solutions for operational efficiency.

As a Senior Machine Learning Engineer, you'll design data pipelines, develop prediction systems, and optimize model deployment processes while collaborating with cross-functional teams.

As a Machine Learning Engineer, you'll design and implement detection systems, enhance model efficacy, and analyze datasets to improve email detection against security threats.

Design and develop scalable AI capabilities, integrating ML models and APIs. Collaborate with teams to ensure solutions meet security and performance standards in cloud environments.

As a Machine Learning Scientist, you'll design and implement frameworks for scientific reasoning using LLMs, collaborate with scientists, and create scalable solutions.

The ML Engineer will build, deploy, and iterate on ML systems, focusing on classification, human feedback loops, and working with real-world data.

The role involves designing scalable distributed systems using Scala, enhancing feature stores for performance, and collaborating with ML engineers to resolve challenges.

The Machine Learning Engineer Intern at Zoox will work on perception systems, developing algorithms for autonomous driving, collaborating with teams, and leveraging advanced machine learning models and datasets.

As an MLE Intern at Zoox, you'll create high fidelity synthetic data, develop AI models simulating road agent behavior, and enhance simulation tools for autonomous driving validation.