Gong harnesses the power of AI to transform how revenue teams win. The Gong Revenue AI Operating System unifies data, insights, and workflows into a single, trusted system that observes, guides, and acts alongside the world’s most successful revenue teams. Powered by the Gong Revenue Graph, AI-powered intelligence, specialized agents, and trusted applications, Gong helps more than 5,000 companies around the world deeply understand their teams and customers, automate critical sales workflows, and close more deals with less effort. For more information, visit www.gong.io.
At Gong, you will join a company built on innovative products, ambitious goals, and passionate people. We are shaping the future of revenue intelligence and we want people who are excited to build what comes next. You will work with a team that dreams big, moves fast, and cares deeply about the craft and about each other. Here, transparency and trust are core to how we operate, and every person has the opportunity to make a visible impact. If you want to grow, stretch, and do work that truly matters, Gong is the place to do the best work of your career.
As a Senior MLOps Engineer at Gong, you'll lead the development and scaling of our machine learning training and AI infrastructure, enabling our AI and Research teams to build, train, and deploy cutting-edge AI solutions at scale. You'll collaborate across research, engineering, and business teams to create the foundations that power Gong’s AI innovation.
You’ll Own:
- Developing and evolving Gong’s machine learning platform, including shared libraries, development standards, CI/CD pipelines, and ML/AI tooling.
- Designing and building scalable infrastructure that supports large-scale model training, experimentation, and validation.
- Driving MLOps strategy and best practices, partnering with cross-functional teams to improve developer productivity, platform reliability, and operational efficiency.
You’ll Solve:
- Scaling machine learning infrastructure to support growing AI workloads, increasingly complex models, and rapid experimentation cycles.
- Creating standardized, efficient workflows that enable research and engineering teams to move from experimentation to production faster and more reliably.
You’ll Impact:
- Accelerate AI innovation by building robust infrastructure that enables teams to develop, train, evaluate and validate models efficiently.
- Improve the scalability, reliability, and consistency of machine learning development across Gong’s AI organization.
How You’ll Succeed Here:
- You bring 8+ years of software engineering experience, including 3+ years of experience building machine learning systems with Python.
- You have strong infrastructure and system design expertise and enjoy solving complex technical challenges end-to-end.
- You thrive in multidisciplinary environments, working across MLOps, DevOps, internal tooling, and AI technologies.
- You balance technical leadership with collaboration, influencing direction while supporting teams and stakeholders across the organization.
*We operate in a flexible hybrid work model.
What makes the AI Platform department at Gong unique?
Here at Gong, we trust and empower our employees with ownership to solve complex problems, make the right decisions, and build the best products that create a radical impact. We call this “Own. Solve. Impact.”
If you are curious to discover Gong's wonderful and challenging world, what are you waiting for? Don’t delay - fill in your application details. Who knows, maybe there’s a Gongster in you!
We encourage our employees to express their personality and identity (whether gender, ethnic, religious, or sexual), and we ensure fairness and equal opportunities. We follow a hybrid working model that combines working from home, on the go, or at the office. This allows us flexibility, autonomy, positive work relationships, and effective work habits.
If these considerations are important to you when choosing a workplace, we'd love to see you with us. To review Gong's privacy policy, visitwww.gong.io/privacy-policy/ for more details.
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