JFrog helps the world’s largest companies deliver software and AI at scale. JFrog ML unifies AI/ML, Security, and DevOps, providing organizations with a trusted platform to manage their entire AI and ML workflows.
At JFrog ML, we support data science teams at every stage of the model lifecycle, from training to serving, with advanced security, governance and deployment capabilities across cloud and self-hosted environments. Our platform streamlines data engineering, enabling teams to ingest, transform and store data for their ML initiatives.
About the role
We’re looking for a Technical Product Manager to shape our AI/ML platform and build the AI infrastructure of the future. This role is ideal for someone who brings technical expertise, a passion for developer-first products and experience with systems that work at scale. You will collaborate closely with engineering and customers to define and build a leading AI/ML platform for developers and data science teams, playing a key role in shaping our SDKs, APIs, and orchestration capabilities.
What you’ll do
- Define cutting-edge ML and AI capabilities, such as:
- A high-performance, scalable model serving engine
- Experiment tracking and model registry
- Advanced ML security features
- Integration with the JFrog ecosystem and external platforms
- Define and lead our user-facing SDKs and APIs.
- Collaborate with developers, designers, solution engineers, and product managers.
- Manage, prioritize and plan features with R&D teams.
- Collect insights from customers and translate feedback into product features.
What we’re looking for:
- 3+ years of experience in technical product management, with a focus on AI/ML, Dev Tools, DevOps, Security or Infrastructure.
- Experience building developer-focused products such as SDKs or cloud infrastructure.
- Familiarity with cloud platforms such as AWS and GCP.
- Strong developer mindset, with a deep understanding of the needs of technical users, data scientists, and engineers.
- Passion for AI/ML and a desire to innovate in MLOps and GenAI applications.
- Proactive, results-driven, and comfortable learning new fields.
Bonus:
- Hands-on experience with MLOps or GenAI workflows.
