Modal
Data AI · GPU cloud
Currently tracking 7 active AI roles, up 13% versus the prior 4 weeks. Primary focus: Serve · Engineering.
Modal currently has 8 active AI-related job listings. The majority of these roles, 75%, are focused on serving infrastructure, with additional positions in agents and data. Engineering roles are most prevalent, with most hiring occurring in the United States. The company is seeking candidates with experience in areas such as inference infrastructure, model serving, and fine-tuning.
Data AI · GPU cloud
Modal currently has 7 active AI-related roles in our index. The most common open titles are: Forward Deployed Engineer - ML (2), Customer Engineer, Forward Deployed Engineer - Systems, Member of Technical Staff - ML Performance, Member of Technical Staff - ML Training Systems. Most positions are in Engineering.
Modal's active AI hiring is concentrated in: serving infrastructure (86%), data (14%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Modal is hiring AI talent in: United States (6 roles), Sweden (1 role).
Job postings at Modal most frequently reference: inference infra, model serving, fine tuning, rl post training, training infra.
In the past 30 days, Modal has posted 0 new AI-related roles.
| Title | Stage | AI score |
|---|---|---|
| Member of Technical Staff - ML Performance Seeking an ML Performance Engineer with 5+ years of experience to optimize ML systems for higher throughput and lower latency. The role involves working with inference engines like vLLM or TensorRT, understanding GPU architecture, and improving ML performance at scale. | Serve | 8 |
| Member of Technical Staff - ML Training Systems The role focuses on engineering for ML training systems, specifically optimizing the training process for production machine learning models, including language models. This involves working with frameworks like PyTorch and high-level training libraries, and optimizing for performance bottlenecks. | Data | 8 |
| Forward Deployed Engineer - ML The Forward Deployed ML Engineer will partner with leading AI companies to help them achieve state-of-the-art performance on demanding AI workloads like LLM serving and model training. This role involves hands-on work with customers to architect and optimize their AI workloads on the Modal platform, contribute to open-source projects, and collaborate with product and sales teams. Requires 2+ years of ML engineering experience, familiarity with serving and training toolchains, and strong communication skills. | ServePost-train | 8 |
| Member of Technical Staff - Product (Backend) Backend engineer for an AI infrastructure company providing GPU access, instant container startups, and storage for training, batch jobs, and low-latency inference. The role involves building modern web applications end-to-end, working across the stack (TypeScript, Python, ClickHouse), and focusing on observability for large-scale AI workloads. | Serve | 7 |
| Customer Engineer Customer Engineer role focused on AI/ML infrastructure, working directly with customers to debug and optimize workloads, while also shipping fixes, features, and automation to improve the core platform. Requires depth in either low-level infrastructure or ML/AI. | ServeData | 7 |