Software Engineer

This work-from-home position at Petuum Inc. is seeking a Software Engineer to build robust and effective modern distributed machine learning systems. The role involves designing, implementing, testing, and debugging backend data and ML pipelines/services, as well as contributing to CASL open-source projects. The Software Engineer will collaborate with Product and Engineering teams to develop new features, write efficient and scalable backend libraries and services, and contribute high-quality open-source software. Additionally, the role requires effectively communicating work to a broader audience through demos and presentations.

• Design, implement, test, and debug backend data and ML pipelines/services
• Collaborate with Product and Engineering teams to develop new features
• Write efficient, reusable, scalable, and testable backend libraries and services
• Contribute high-quality open-source software to simplify distributed ML programming
• Communicate work to a broader audience through demos and presentations

• Experience in building robust, effective, and well-packaged modern distributed machine learning systems
• Familiarity with CASL open-source projects
• Proficiency in designing, implementing, testing, and debugging backend data and ML pipelines/services
• Ability to work with Product and Engineering teams to build new features
• Strong skills in writing efficient, reusable, scalable, and testable backend libraries and services
• Contribution of high-quality open-source software to simplify distributed ML programming
• Excellent communication skills to present work to a broader audience through demos and presentations

• Work-from-home position with the ability to telecommute
• Building robust, effective, and well-packaged modern distributed machine learning systems
• Contribution to CASL open-source projects
• Designing, implementing, testing, and debugging backend data and ML pipelines/services
• Collaboration with Product and Engineering teams to build new features
• Writing efficient, reusable, scalable, and testable backend libraries and services
• Contribution of high-quality open-source software to simplify distributed ML programming
• Communication of work to a broader audience through demos, presentations, and blog posts