Top Machine Learning Engineer Jobs

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.

The Principal Machine Learning Engineer will lead the technical efforts to enhance search quality through data-driven methods, optimizing AI-driven search systems and collaborating with cross-functional teams.

Lead AI-ML and Data Engineering teams for federal clients, managing AI workflows and the machine learning lifecycle using Azure tools, while ensuring compliance and effective stakeholder communication.

As an ML Engineering Intern, you'll develop generative AI solutions, contribute to product development, and collaborate with cross-functional teams.

The Machine Learning Engineer will apply extensive experience in machine learning and data science, focusing on model deployment, data analysis, and causal inference within production environments.

The role involves developing ML-based planning algorithms for autonomous trucks, ensuring safety checks, real-time operation, and keeping up with research. Requires strong communication and collaboration.

As a Machine Learning Engineer, you'll develop and implement machine learning algorithms, collaborate with teams, and mentor others while maintaining a strong focus on computer vision projects.

Design and deploy machine learning systems for autonomous vehicles, collaborating with teams to improve model performance and safety using real-world data.

As a Summer Intern, you'll prototype ML models for edge intelligence, support data engineering, and optimize models for embedded systems, collaborating across engineering teams.

As a Machine Learning Engineer, you will train, test, deploy, and maintain ML models, define solutions for mission-critical systems, and collaborate with engineers and data scientists.

The role involves developing ML systems for enterprise workflows, focusing on user understanding, task prediction, and optimizing ML pipelines. Key responsibilities include designing scalable evaluation frameworks and collaborating with teams to deliver production-ready solutions.

The Machine Learning Engineer will develop and improve ML models for product surfaces, build data processing pipelines, and leverage machine learning technologies in advertisements.

Develop and maintain AI/ML interfaces, collaborate with cross-functional teams, and ensure high performance and reliability of AI systems.

The Software Engineer will develop and optimize interfaces for AI/ML tools, collaborating with various teams to ensure high performance and reliability.

The Software Engineer will develop and optimize AI/ML interfaces, collaborate with teams, design APIs, and implement solutions while ensuring performance and reliability.

As a Software Engineer, you will develop and optimize AI/ML interfaces, collaborate on deployment, and ensure system reliability. Responsibilities include API design, debugging, and maintaining scalable solutions, while keeping up with AI trends.

You will own the compilation stack transforming AI models into optimized inference for autonomous driving. This includes developing tools and techniques for model export and optimizing performance while ensuring safety and reliability.

The Senior Compiler Engineer will develop a model compilation toolchain for deploying optimized machine learning models in autonomous vehicles, focusing on performance engineering and collaboration with cross-functional teams.

The role involves designing, implementing, and optimizing CUDA-based kernels for autonomous vehicles, ensuring high-performance ML inference for AV software.

The Senior ML/AI Engineer will enhance developer productivity for AV engineers at GM by designing, implementing scalable, reliable systems and mentoring team members.

As a Senior Machine Learning Engineer, you will design and build ML models for patient-provider matching, focusing on personalization and ranking. Responsibilities include model development, A/B testing, and collaborating across teams to improve patient experiences.

Develop and maintain machine learning models for user safety, design scalable systems, and collaborate on AI solutions while ensuring fairness. Requires strong programming and domain expertise in ML technologies.

Join Sajix as a Machine Learning Engineer Trainee to assist in building and deploying ML models for healthcare solutions, collaborating with data scientists, and gaining hands-on experience.

The Machine Learning Engineer will develop Deep Learning technologies for Computer Vision, SAR, and Geospatial Exploitation, impacting U.S. government issues.

The Machine Learning Engineer will develop deep learning technologies for computer vision and SAR, implementing models and augmenting data processing methods.