About Modular
At Modular, we’re on a mission to revolutionize AI infrastructure by systematically rebuilding the AI software stack from the ground up. Our team, made up of industry leaders and experts, is building cutting-edge, modular infrastructure that simplifies AI development and deployment. By rethinking the complexities of AI systems, we’re empowering everyone to unlock AI’s full potential and tackle some of the world’s most pressing challenges.
If you’re passionate about shaping the future of AI and creating tools that make a real difference in people’s lives, we want you on our team. You can read about
our culture and
careers to understand how we work and what we value.
About the role:
Modular is building a next-generation AI infrastructure platform that unifies fragmented application frameworks and hardware backends into a single, programmable system – making it easier to deploy AI in production while accelerating innovation across models and hardware. We’re looking for someone to drive the product vision for Modular’s cloud compute platform: a high-performance, scalable AI model-serving system designed for advanced GenAI developers, with deep visibility and control over performance, cost, and execution. In this role, you’ll work closely with engineering, program management, and technical writing to turn cutting-edge infrastructure into real customer value, evolve the platform from early adoption into a scalable cloud business, and collaborate with leading AI companies and hardware partners as we redefine modern AI infrastructure through a more transparent, performance-driven cloud.
LOCATION: Candidates based in the US or Canada are welcome to apply. You can work in our office in Los Altos, CA or remotely from home. Onboarding for new hires is conducted in-person in our Los Altos, CA office.
What you will do:
- 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.
What you bring to the table:
- 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.
Helpful, but not required:
- 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.
What Modular brings to the table:
- Amazing Team. We are a progressive and agile team with some of the industry’s best engineering and product leaders.
- World-class Benefits. In order to attract the best, we need to offer the best. Premier insurance plans, up to 5% 401k matching, flexible paid time off, and more are available to you! Please note that specific benefit packages may vary based on your location.
- Competitive Compensation. We offer very strong compensation packages, including stock options. We want people to be focused on their best work and believe in tailoring compensation plans to meet the needs of our workforce.
- Team Building Events. We organize regular team onsites and local meetups in Los Altos, CA as well as different cities. Traveling 2-4 times a year is expected for all roles.
Working at Modular will enable you to grow quickly as you work alongside incredibly motivated and talented people who have high standards, possess a growth mindset, and a purpose to truly change the world.
The estimated base salary range for this role to be performed in the US, regardless of the state, is $234,000.00 - $286,000.00 USD.
The estimated base salary range for this role to be performed in Canada, regardless of the province, is $229,000.00 - $280,000.00 CAD.
The salary for the successful applicant will depend on a variety of permissible, non-discriminatory job-related factors, which include but are not limited to education, training, work experience, business needs, or market demands. This range may be modified in the future. The total compensation for a candidate will also include annual target bonus, equity, and benefits, with equity making up a significant portion of your total compensation.
For candidates who fall outside of the listed requirements, we nevertheless encourage you to apply as we may have openings that are lower/higher level than the ones advertised.