Top Machine Learning Engineer Jobs

Lead the development of deep learning sensing technology by designing and deploying computer vision models for real-time inference, optimizing for edge deployment, and establishing MLOps pipelines.

The Staff Machine Learning Engineer will develop and deploy advanced AI models and systems, enhance GenAI capabilities, and collaborate with cross-functional teams.

Develop and implement machine learning models for evaluating disputes and chargebacks, and create a model orchestration layer. Collaborate on data use for enhanced user experiences.

Design and implement production-grade AI features to enhance recruiting efficiency, utilizing AI/ML technologies for intelligent candidate search and insights extraction.

As a Machine Learning Infrastructure Engineer, you will build and maintain infrastructure for ML model training, optimize deployment, collaborate across teams, and improve internal tools for ML workflows.

The role involves developing and deploying large language models for healthcare, applying advanced ML techniques, and collaborating with interdisciplinary 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.

The Machine Learning Engineer will develop editable visuals combining computer vision and machine learning, enabling chat-driven figure editing and leveraging biological understanding to produce accurate visuals.

Develop and deploy end-to-end machine learning solutions, collaborate with cross-functional teams, and implement MLOps frameworks while monitoring model performance in production.

The Senior Staff Machine Learning Engineer will lead the design and implementation of ML systems, leveraging Generative AI and guiding teams to enhance customer experiences and improve decision-making in the Claims organization.

Lead the design, development, and implementation of advanced machine learning models, optimizing pipelines, and collaborating with teams to enhance products.

The Machine Learning Engineer will design, develop, and deploy ML models using Google Cloud tools, focusing on Document AI and Vertex AI, ensuring scalable applications and efficient performance.

The Senior Machine Learning Engineer will develop advanced fraud prediction models, utilizing anomaly detection and supervised learning techniques to enhance fraud prevention efforts and collaborate with cross-functional teams to integrate these models into the organization's systems.

The Senior Machine Learning Engineer will develop NLP solutions, manage datasets, optimize performance metrics, and work on ML applications for healthcare.

As a Machine Learning Engineer in Computer Vision, you'll develop AI solutions using advanced algorithms, focusing on image classification, segmentation, and video processing tools.

The ML Engineer will leverage deep learning for natural language processing tasks, impacting Entefy's products while requiring strong machine learning fundamentals and NLP expertise.

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.

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.