Infrastructure Engineer (AI)

Location: Hybrid in Mountain View, California, United States

Company

hirify.global is an applied AI research lab building data and reinforcement learning environments for training and evaluating agents.

What you will do

• Design and own the sandboxing and execution layer for realistic, multi-tool RL environments.
• Build snapshot, restore, inspection, and branching capabilities for disk, process, memory, and accelerator state where relevant.
• Develop failure detection and recovery systems for reward hacks, infrastructure faults, and fairness issues.
• Extend execution to long-horizon and multi-node environments, optimizing throughput, latency, utilization, and cost per rollout.
• Build the framework for specifying, packaging, deploying, debugging, and observing RL environments across thousands of concurrent rollouts.
• Scale prototypes into reproducible production systems and create documentation and tools for internal and external users.

Requirements

• Production systems or research infrastructure experience at scale, including distributed systems, execution engines, or container and sandboxing infrastructure.
• Strong knowledge of containers, isolation, namespaces, cgroups, virtual machines, filesystems, process management, and state management.
• Experience with profiling, scheduling, resource utilization, cost optimization, and distributed computing.
• Proficiency with cloud platforms such as GCP or AWS.
• Strong Python skills and a systematic approach to testing, validation, and reliability.
• Excellent communication skills and the ability to translate research needs into infrastructure requirements.

Nice to have

• Experience with RL training or evaluation infrastructure and agent rollout execution layers.
• Experience with checkpointing, snapshot-restore systems, CRIU, or distributed state management.
• Rust, Go, or C++ experience.
• Background in high-throughput, low-latency execution systems or research engineering at an AI or systems-focused company.
• Contributions to infrastructure, datasets, benchmarks, or open-source systems.

Culture & Benefits

• Work closely with research and data teams.
• Collaborate directly with frontier AI labs and enterprise customers.
• Health coverage is provided.
• Compensation includes salary and equity.