Top Machine Learning Jobs

As a Machine Learning Engineer, you'll develop and ship models for an AI platform, own projects from start to finish, and work closely with customers to enhance product features.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

The Machine Learning Engineer will scale core infrastructure, manage data pipelines and model evaluation, and improve benchmarking systems. Collaborate with teams to enhance AI evaluation methodologies.

The Machine Learning Engineer will develop intelligent features to enhance code security using LLMs, collaborate with researchers, and manage ML models on AWS.

As an Applied Scientist II, you will work with cross-functional teams on projects that optimize software systems and improve ML components, while analyzing inefficiencies and proposing solutions.

Develop and implement machine learning solutions for Supply Chain infrastructure, guiding projects from conception to operationalization and collaborating with global teams.

Manage and lead a team in developing machine learning algorithms for driving models. Oversee strategy, technical guidance, performance monitoring, and resource allocation for Offline ML models.

The Principal ML Engineer will define and lead the ML architecture and strategy, solve complex challenges, and mentor engineers across the company.

Seeking an experienced Machine Learning Engineer to design and deploy scalable machine learning and NLP solutions, mentor junior engineers, and collaborate on data-driven projects with cross-functional teams.

The Principal AI/ML Engineer will develop machine learning models for campaign optimization in AdTech, collaborating across engineering and product teams to enhance advertising capabilities.

Develop advanced ML models for an advertising platform, focusing on performance and scalability. Lead technical strategy and collaboration across teams to enhance campaign automation and optimization.

The Principal AI/ML Engineer will lead the design and implementation of machine learning solutions in AdTech, focusing on campaign optimization and user personalization while also mentoring other engineers.

Conduct research and develop machine learning models for finance, focusing on deep learning and large language models, optimizing them for performance, and collaborating with teams to integrate ML solutions.

Design and maintain ML pipelines and data pipelines, optimize fraud detection models, collaborate with teams, and ensure data quality for high-scale applications.

As a Staff Machine Learning Engineer, you will design and develop ML systems to combat fraud by building data pipelines, integrating data sources, and ensuring high-quality model performance while collaborating with teams.

Software Engineers will design, implement and deploy ML solutions while collaborating across teams to enhance military capabilities and operational outcomes. Responsibilities include coding, debugging, and addressing user needs while traveling up to 30% for hands-on deployments.

The Senior Machine Learning Engineer will design and build scalable AI/ML infrastructure, collaborate on model development, and optimize performance in distributed training environments.

Lead the Content Engineering team, defining technical strategies and architecture while driving large-scale ML projects and ensuring Trust capabilities on the Pinterest platform.

Develop electrical system ontology for data centers, utilize monitoring tools, create anomaly detection models, and collaborate with teams on insights and strategies for optimization.

Lead development and deployment of advanced ML models for heart disease diagnostics, providing technical leadership and guiding projects through regulatory approval and clinical integration.

Machine Learning Engineers at Tennr will architect, train, deploy models, optimize data pipelines, integrate ML into backend systems, and collaborate with teams for product evaluation.

As a Software Engineer intern, you'll work on AI-driven projects spanning data management, onboard systems, ML infrastructure, simulations, and technical infrastructure, collaborating with experts in various fields.

Lead a 130-person ML organization focused on Ads performance, developing technical strategies and improving modeling systems and marketplace health.

The Applied Scientist will design and implement machine learning models, collaborate across teams, improve model performance, and contribute to internal research initiatives.

The role involves advanced data analysis, designing data solutions, developing machine learning models, collaborating across teams, and providing strategic insights to improve business decisions.