Why This Job is Featured on The SaaS Jobs
This Senior MLOps Engineer role sits at the infrastructure layer of a SaaS company where machine learning is a core product capability rather than an experiment. The remit spans platform standards, shared tooling, and training infrastructure, which are increasingly critical as SaaS products embed AI features and need reliable paths from research to production. For the wider SaaS ecosystem, this is a signal role where operational excellence directly shapes how quickly AI can be shipped and maintained.
Career-wise, the position offers durable SaaS leverage by building internal platforms that multiple teams depend on. Experience here translates across AI-forward SaaS companies because it touches the recurring challenges of reproducibility, CI/CD for ML, governance of experimentation, and scaling compute without sacrificing reliability. The cross-functional collaboration with research, engineering, and business stakeholders also mirrors how modern SaaS organisations operationalise AI beyond a single team.
This role tends to suit engineers who prefer enabling others through frameworks, pipelines, and guardrails, while still owning complex system design end to end. It aligns with professionals who enjoy setting technical direction through best practices and who are comfortable operating at the boundary between DevOps, ML engineering, and internal developer productivity.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
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, visit www.gong.io/privacy-policy/ for more details.
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