Modal

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.

Forward Deployed ML Engineer to partner with leading AI companies and foundation model labs to help them achieve state-of-the-art performance on demanding workloads like LLM serving, model training (SFT, RLHF), and audio pipelines. This role involves hands-on optimization, contributing to open-source projects, and collaborating with product/sales teams.

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.

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.

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.

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.

Modal is an AI infrastructure company that provides GPU access, fast container startups, and native storage for training models, running batch jobs, and serving low-latency inference. They are seeking an Infrastructure Security Engineer to design and secure their core systems, focusing on building security into their multi-tenant, cloud-native platform. The role involves securing isolation mechanisms, container orchestration, identity and access management, secrets management, and cloud environments, working closely with engineering teams to ensure resilience and trustworthiness.

Modal is an AI infrastructure company seeking a Security Field Engineer to manage external security communications, engage with customer security teams, and drive improvements in security posture. This role involves technical discussions, responding to security reviews, and partnering with engineering to implement changes. The ideal candidate has experience in security engineering or GRC, understands cloud architectures, and can communicate complex security concepts effectively.

Modal is seeking a Systems Engineering Manager to lead a team focused on building and scaling AI infrastructure. This role involves both technical contributions and people management, with a focus on distributed computing, large-scale data handling, and performance optimization for AI workloads like model training and inference serving.

Modal is an AI infrastructure company that provides GPU access, instant startups, and native storage for training models, running batch jobs, and serving low-latency inference. They are seeking a Member of Technical Staff - Platform Engineering to focus on reliability, performance, and availability as the first reliability-focused hire. The role involves identifying architectural improvements, fostering a reliability culture, designing operational processes, participating in on-call rotations, building monitoring systems, and debugging production issues. Requirements include 5+ years of production code experience, 2+ years of on-call experience, strong cloud skills (AWS preferred), familiarity with scaling and capacity planning, and experience with Kubernetes is a plus. Systems safety research and control theory experience are also a plus.

This role is a Forward Deployed Engineer focused on technical sales for an AI infrastructure platform. The FDE will partner with sales to understand customer needs, design solutions using Modal's platform, and support enterprise sales cycles. Key responsibilities include technical discovery, solution architecture, demos, proof-of-concepts, and addressing security/compliance concerns. The role requires deep experience with cloud platforms, containerization, databases, and an understanding of ML/AI infrastructure challenges.

Modal is seeking Forward Deployed Engineers to work on the intersection of deep infrastructure and customer impact. This role involves partnering with AI companies to design and ship production infrastructure on Modal's platform, focusing on cloud architecture, networking, storage, containerization, and sandboxing. Responsibilities include architecting and deploying large-scale production workloads, leading technical discovery, migrating customers from existing cloud infrastructure, and collaborating with product and sales teams.

Modal is seeking a strong engineer with experience building developer tools, specifically Python libraries, to enhance developer productivity for AI teams. The role involves working on infrastructure for AI workloads, including model training, batch jobs, and inference serving.

The role focuses on building and maintaining the high-performance systems that power Modal's serverless AI infrastructure, including GPU access, container startups, and inference serving. It requires strong experience in distributed systems, cloud, and low-level OS foundations, with an emphasis on performance engineering.

Modal is seeking a Security GRC Specialist to own and scale its security and compliance programs. This role will work closely with engineering and product teams to build customer trust, enable sales, and meet regulatory expectations. Responsibilities include managing compliance frameworks (SOC 2, ISO 27001, GDPR), driving audits, responding to customer security questionnaires, and collaborating with engineering to implement security controls. The ideal candidate has 3-7+ years of experience in security GRC, a technical mindset, and strong execution skills.

The role is for a systems engineer to build and maintain the high-performance serverless platform that powers AI workloads, focusing on GPU access, container startups, and inference serving. It requires strong experience in distributed systems, cloud, and low-level OS foundations, with an emphasis on performance engineering.

Modal is seeking a frontend engineer to build and ship modern web applications end-to-end, focusing on complex and gorgeous products with a high degree of customer empathy, product sense, and ownership. The role involves using modern JavaScript frameworks like React, building pixel-perfect components, and partnering closely with product design and customers to solve problems. The engineer will also participate in on-call rotations and respond to production incidents.