Dialpad is hiring a
Software Engineer

Summary

Join Dialpad's Ai Engineering team as a Software Engineer–Ai Core, working on the development and uptime of Dialpad's proprietary near real-time ML inference system. You'll contribute to powering Dialpad's Ai products at scale, collaborating with Data Science teams to unleash Ai features that work for our customers.

Requirements

• Have a Bachelor’s Degree in Computer Science, Mathematics, Software Engineering, or a related field, or equivalent work experience
• Have 5+ years of experience in similar roles
• Have strong fundamentals in software engineering and computer science
• Be excited to work on a distributed team; you value collaboration whether your teammate sits beside you or across an entire continent
• Have strong experience working with one or more dynamically typed programming language(s)
• Have a strong desire to continuously learn
• Enjoy 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
• Fluency in English

Responsibilities

• Acclimate and be paired directly with a peer (in addition to your manager) whose job it will be to make sure you have the information and tools you need to be successful
• Work primarily with fully asynchronous modern Python, but we are strong believers in using the right tool for the job, making use of other languages where it makes sense to in our stack
• Be exposed to Open Source Software. We employ many Open Source technologies to get the job done, and we love to contribute back to those communities. We also maintain Open Source codebases for libraries we’ve created ourselves
• Collaborate. All levels of engineers on the team participate in authoring and reviewing PRs for code changes, and RFCs for more major system changes
• Have the opportunity to deploy code daily on Google Cloud Platform using modern best practices like Kubernetes, Docker, and CI/CD Systems
• 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. Exploring knowledge and findings with teammates is highly encouraged, with weekly opportunities to host or attend learning sessions including members of both Engineering and Data Science teams

Benefits

Professional development