Join Our Innovative Team as a Software Engineer, ML Ops at Dialpad

About Dialpad - Work Beautifully

Dialpad is the leading AI-Powered Customer Intelligence Platform that is revolutionizing how the world collaborates. With over 4 billion minutes of voice and meeting analysis, Dialpad offers a unified workspace combining advanced AI technologies like AI Contact Center, AI Sales, AI Voice, AI Meetings, and AI Messaging. Trusted by over 30,000 brands globally, Dialpad utilizes real-time AI insights to enhance productivity and customer satisfaction. With strong backing from Google and prominent venture capitalists like ICONIQ and Andreessen Horowitz, our company boasts over $200M in ARR and ranks among the fastest-growing AI firms worldwide.

About the Team

At the heart of Dialpad, our AI Engineering team works closely with Data Science, Telephony, and Product Engineering teams to innovate The Good AI. In this role, your expertise will span across Distributed Systems Engineering, DevOps, MLOps, and Data Engineering, significantly impacting our pioneering AI products.

Your Role and Impact

As a Software Engineer specializing in ML Ops, you'll have ownership of the development and maintenance of Dialpad’s proprietary near real-time ML inference system. This large-scale distributed system is crafted using cutting-edge technologies such as Kubernetes, Redis, event-driven message bus systems, modern asynchronous Python, and various Open Source technologies. Your contributions will be crucial in enhancing Dialpad's AI-driven products, ensuring they deliver exceptional functionality to our customers.

This position offers the flexibility to be based in our Buenos Aires, Argentina office or to work fully remotely within GMT-8 to GMT-3 time zones, reporting directly to the Engineering Manager of AI Engineering.

What You'll Do

First 3 Months:

• Acclimate through direct pairing with peers and your manager to integrate seamlessly into our processes.
• Engage with modern asynchronous Python and other programming languages, tailored to our technological stack’s needs.
• Interface and contribute to Open Source Software, enhancing both community and in-house projects.

First 6 Months:

• Participate actively in coding reviews and propose system advancements through RFCs.
• Deploy code daily using Google Cloud Platform, Kubernetes, Docker, and CI/CD systems.
• Adopt new technologies and methodologies to maintain our systems' scalability and fault tolerance.

First 12 Months:

• Develop and manage high-performance data pipelines, taking strategic ownership of system components.
• Share your knowledge and learnings across the team through regular learning sessions.

Skills You'll Bring

You are suited for this role if you have a Bachelor’s degree (or equivalent experience) in Computer Science, Mathematics, or Software Engineering, backed by strong engineering and computer science fundamentals. Your proficiency in dynamically typed programming languages and a passion for distributed team collaboration will drive success in this role. Your approach is data-driven, focusing on continuous learning and efficient problem-solving.

Bonus Skills

Experience with the Python ecosystem, cloud platforms like Google Cloud or AWS, and familiarity with git, database systems, and data pipelines will be advantageous.

Dialpad's Culture, Compensation, and Benefits

Recognized seven times as a Top Workplace, Dialpad thrives on a culture that celebrates collaboration, innovation, and inclusivity. We offer competitive compensation, equity options, and a comprehensive benefits package that underscores our commitment to our team's professional and personal growth. Additionally, our robust DEI initiatives ensure every team member’s voice is heard and valued.

Dialpad is an equal opportunity employer committed to diversity and inclusion. We encourage candidates from all backgrounds to apply, especially those who may not meet every single requirement.

Ready to transform the way the world works? Apply today and be a part of Dialpad's journey to innovate continuously and work beautifully.