Top Machine Learning Engineer Jobs

As a Staff Machine Learning Engineer, you will design, build, and deploy ML systems, optimize performance, and collaborate with teams to integrate AI solutions.

The Machine Learning Engineer at Lyft will design, build, and deploy ML models across various domains, collaborating with data scientists and product managers to solve complex business problems at scale.

The Staff Machine Learning Engineer will design and implement ML systems, build scalable architectures, collaborate with data teams, and drive technical strategy for AI applications.

The Staff Data Architect will design complex data solutions, lead data architecture initiatives, and oversee data governance while collaborating with various teams to meet business objectives.

The role involves designing and implementing AI and ML systems for the Defense and Intelligence sectors, focusing on data accessibility and operationalization of models.

The role involves developing AI technologies for customer support at Airbnb, leveraging ML systems to enhance customer experience through innovative solutions.

As a Senior ML Engineer, you'll design and deploy advanced machine learning systems for autonomous vehicles, ensuring real-time performance and robustness in diverse conditions. You'll lead technical projects, mentor engineers, and collaborate across teams to enhance onboard capabilities.

As a Software Engineer II, you'll develop backend systems, support ML platform features, collaborate across teams, and ensure system availability.

As a Machine Learning Engineer Intern, you will work on advanced projects involving 3D perception, data engineering, and audio signal processing for autonomous vehicles, alongside a mentor.

You will create large datasets and training recipes, develop methods for data mining, create scalable infrastructure solutions, and collaborate with ML infrastructure teams.

Analyze ML resource usage, develop dashboards for monitoring metrics, optimize workflows, and guide ML engineers on best practices.

As a Senior Developer, you will build and evolve ML/AI applications on AWS, collaborating with teams to deliver effective solutions and ensure model accuracy.

Responsible for building and evolving ML/AI applications on AWS, integrating machine learning solutions, and managing automated pipelines for deployment and performance monitoring.

As a Senior Developer, build and deliver scalable ML/AI applications on AWS, collaborating with teams to meet business needs and continuously improve solutions.

The AI/ML Engineer I will design, develop, and optimize scalable AI solutions using machine learning models, ensuring performance and reliability while collaborating with teams.

As a Lead Machine Learning Engineer, you will design, build, and optimize ML applications, collaborate with teams, and ensure model performance.

The Lead Machine Learning Engineer will design, build, and productionize ML applications, oversee model performance, collaborate with teams, and ensure reliable deployment of ML systems at scale.

As a Lead Machine Learning Engineer, you'll design, develop, and implement ML applications, collaborating with teams to ensure high performance and scalability of ML systems.

Design and maintain infrastructure for large-scale multimodal training and evaluation. Collaborate with researchers to build reliable distributed data systems.

The Principal AI/ML Engineer will lead the design, implementation, and deployment of AI systems, mentor junior engineers, and ensure model performance and reliability in production environments.

The Staff Machine Learning Engineer will lead AI initiatives, architect LLM systems, design evaluation frameworks, and mentor engineers.

As an ML Engineer specializing in inference, you will optimize models for production, implement neural network techniques, and collaborate with researchers.

As an ML Engineer at Hilbert, you will build and deploy innovative machine learning systems for enterprise clients, translate business needs into modeling decisions, and own projects from conception to production deployment, focusing on B2C environments.

Develop and integrate AI solutions for government customers, focusing on machine learning and deep learning technologies. Collaborate with teams and mentor juniors while providing technical reports.

Develop AI/ML models for 3D simulation and geology prediction, refine data pipelines, and integrate deep learning tech with product backend.