Top Entry Level DevOps Jobs

As a Software Engineer at Carvana, you'll develop scalable web applications, contribute to cross-functional projects, write maintainable code, work with databases, utilize cloud systems and Kafka for data streaming, and collaborate with teams to enhance user experience while staying current with technology trends.

The Software Engineer new grad will work on building tools to facilitate contributor growth, develop fraud-detection systems, optimize task-labeler matching, and create new AI infrastructure products for handling large volumes of data. They will engage in full-stack web app development while ensuring product quality and performance at scale.

The Controls Engineer supports the Automation Control team by resolving control issues in live operational systems, modifying PLC code, conducting maintenance, and analyzing data to enhance performance. They may work on hardware faults, conduct inspections, and support site operations during training and startup phases.

Seeking a skilled and motivated Robot Manipulation Engineer with expertise in modern robotics and manipulation to join the AI - Manipulation team at Path Robotics. Responsibilities include designing and implementing advanced manipulation algorithms, developing learning-based methods for motion control, collaborating with cross-functional teams, and staying updated with the latest advancements in robotics. Candidates should have a Master's degree or Ph.D. in Robotics or related field, experience with machine learning techniques, strong programming skills, and proficiency in reinforcement learning techniques.

The Geospatial Solutions Engineer will support ArcGIS Enterprise applications, troubleshoot client issues, design cloud-based GIS solutions, implement automation for GIS tasks, and develop data-driven solutions for national security operations, primarily interacting with Esri applications.

The HPC Engineer will handle the configuration and maintenance of HPC systems, including hardware issues, software installation, and preventive maintenance. This role requires scripting skills, knowledge of operating systems, and a strong understanding of network configurations.

The AI/ML Ops Engineer will create and maintain data pipelines, implement machine learning models to enhance products, and collaborate with cross-functional teams to align data science efforts with business objectives, ensuring data-driven innovation in customer experiences.