Builds technical support for AI/ML workloads by shipping code, automating fixes, and directly assisting customers with debugging and optimization. Requires deep expertise in low-level infrastructure or AI/ML engineering with strong communication skills.
150k – 230k/yr
HybridSupport Engineering
About the role
Responsibilities
Ship code that matters: fix bugs, build features, and create automation that improves the experience for every Modal user.
Work directly with customers: help developers and ML engineers debug, optimize, and architect their workloads across Slack, email, and calls.
Build scalable systems: design tooling, dashboards, and automated workflows that make support efficient at scale.
Close the feedback loop: translate patterns into docs fixes, API changes, or new feature proposals.
Contribute to open source and technical content: write examples, build demos, and publish content.
Requirements
Depth in low-level infrastructure (operating systems, file systems, networking, performance profiling, cluster management, distributed systems) or AI/ML engineering (training models, optimizing inference, GPUs, ML infrastructure), with familiarity in the other.
Automation mindset to eliminate manual processes.
Clear communicator for explaining issues, writing bug reports, and documentation.
Support Operations Engineer owns customer interactions end-to-end, identifies recurring issues for product/engineering improvements, maintains AI-powered knowledge bases and support tooling, and analyzes data for operational enhancements in a B2B tech environment.
150k – 180k/yr
HybridSupport Engineering
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