Modular is on a mission to revolutionize AI infrastructure by rebuilding the AI software stack. The role involves driving the product vision for Modular’s cloud compute platform, collaborating with engineering and partners to enhance AI deployment and performance.
Responsibilities:
- Own the product vision and strategy for Modular’s Cloud Platform, grounded in real customer workloads and measurable business outcomes
- Partner with engineering and leading AI application teams to design and deliver a high-performance, transparent AI serving platform, giving customers deep visibility and control over performance, cost, and execution
- Define and manage roadmaps, milestones, and success metrics, balancing near-term delivery with long-term platform evolution
- Drive customer- and data-informed prioritization, translating market signals, performance insights, and feedback into clear product decisions and trade-offs
- Work cross-functionally with engineering, program management, technical writing, design, and GTM to deliver a cohesive end-to-end cloud product experience
- Engage directly with advanced enterprise customers and partners to validate direction, support early deployments, and feed learnings back into the platform
- Identify and advance strategic integrations across hardware, cloud, and ecosystem partners while preserving performance and programmability as first-class principles
Requirements:
- 9+ years of product management experience, including significant work on technical cloud platforms, AI infrastructure, or data systems, or equivalent experience as a software or AI systems engineer
- Strong understanding of cloud architectures and technologies (e.g., Kubernetes), and/or experience with AI infrastructure platforms such as PyTorch, vLLM, CUDA, Vertex AI, SageMaker, or similar systems
- Experience defining product vision, shaping roadmap trade-offs, and driving products from early adoption toward broader production use
- Familiarity with security, privacy, and compliance considerations for cloud platforms
- Strong analytical and systems-level thinking, with the ability to reason about performance, scalability, and cost
- Excellent written and verbal communication skills, especially when working across technical and non-technical audiences
- A growth-oriented mindset with a bias toward learning from customers, data, and real-world usage
- Master's degree or Ph.D. in Computer Science or related technical field
- Experience developing, training, and/or deploying machine learning models into production environments
- Have worked in or around startups before or have a strong understanding of the nature of fast-moving, highly dynamic teams