Software Engineer, Dialpad

• Bachelor’s Degree in Computer Science, Mathematics, Software Engineering, or a related field, or equivalent work experience
• Strong fundamentals in software engineering and computer science
• Experience working on a distributed teams
• Strong background working with one or more dynamically typed programming language(s)
• Enjoyment of efficient evaluation of a problem space and finding the right tool for the job
• Measure & monitor everything ensuring stability, redundancy, and runtime
• Make data-driven decisions - Measure twice, cut once
• Enjoy learning from your experiences and sharing your knowledge with your team
• Work on diverse problems across different systems
• Appreciate code and system maintainability, and support continuous improvement

Desirable

• As a Software Engineer–Ai Core, you’ll work with the team to own the development and uptime of Dialpad’s proprietary near real-time ML inference system, a large-scale distributed system built by leveraging technologies like Kubernetes, Redis, event-driven message bus systems, modern asynchronous Python, and a plethora of Open Source technologies.
• You’ll contribute directly to powering Dialpad’s Ai products at scale, working closely alongside the Data Science teams to unleash Ai features that work for our customers.
• Work primarily with fully asynchronous modern Python, Java, C++, and Cython
• Support the deployment of our AI Models and develop innovative solutions to that process
• Author and review PRs for code changes, and RFCs for more major system changes
• Deploy code daily on Google Cloud Platform using modern best practices like Kubernetes, Docker, and CI/CD Systems
• Use and make contributions to Open Source technologies, maintaining our own Open Source codebases
• Work with the team to continuously learn by constantly evaluating and applying state-of-the-art systems and techniques to ensure we build systems which are fault tolerant and highly scalable
• Build and manage high-performance real-time data pipelines, taking significant ownership of key components of the stack
• Share and explore knowledge and findings with teammates frecuently through hosting or attending learning sessions with cross-functional teams