Top DevOps Jobs

The Applied Systems Engineer will develop new products and coordinate order fulfillment activities while collaborating with various teams. Responsibilities include project management, technical documentation review, test planning, and ensuring product delivery aligns with customer specifications and timelines.

The R&D Engineering Manager leads a team to develop and test new valve, actuator, and positioner products, ensuring alignment with organizational goals. Responsibilities include managing technical aspects of projects, coordinating with various teams, overseeing testing and certification, and supporting global innovation initiatives.

The Process Engineer role focuses on enhancing efficiency, reducing costs, and improving safety through data-driven improvements in manufacturing processes. Responsibilities include evaluating production processes, managing CAPEX projects, improving RCCA processes, and ensuring standard work documentation. Additionally, the role promotes a strong HSE culture and requires minimal travel for training and collaboration.

The Senior Front-End Technology Lead is responsible for designing and writing code, performing code reviews, and developing technical documentation. They act as technical leaders, ensuring project performance and client relations, coordinating technical communication, and mentoring junior teammates. They oversee technical architecture, manage software release activities, and provide training programs.

The Front-End Developer (FED) is responsible for completing front-end tasks and providing support to web applications. Responsibilities include collaborating on data exchange, translating designs into code, troubleshooting issues, and ensuring documentation is maintained. Required skills include proficiency in HTML5, JavaScript, CSS, working with email development, and using Adobe Campaign. A bachelor's degree in Computer Science or related technical discipline is preferred.

The Senior Data and ML Infrastructure Engineer will design and optimize large-scale data platforms and machine learning infrastructure, lead infrastructure tooling improvements, implement ML Ops capabilities, and drive optimization projects for cost savings while maintaining service performance. This role requires engagement in on-call rotations to resolve complex issues.