Research Engineer – Training and Environment Infrastructure

Max Corporate Group•San Francisco, CA

1d•Hybrid

About The Position

MaxIT Consulting – Max Corporate Group is hiring a Research Engineer to build training and environment infrastructure for a fast-growing AI company in San Francisco. The company develops evaluation environments and post-training infrastructure for long-horizon enterprise agents, and uses that stack to train and deploy custom models for large technology companies. It is a small, founding-stage team with experience from leading AI labs and technology companies, and it is already profitable with enterprise revenue. The role owns systems that enable long agent runs to be paused, rewound, and continued, as well as infrastructure to start, monitor, and shut down thousands of heterogeneous environments reliably and cost-effectively. Research and deployed teams rely on this infrastructure. Within the first 90 days, the successful candidate will own a core system end to end: checkpoint and restore, the environment orchestrator, or simulated companies used for training and evaluation. The position is full-time, permanent, and hybrid, with three to four days per week in the San Francisco office. The schedule is a six-day work week. The start date is ASAP. Candidates must be legally authorized to work in the United States. New visa petitions are not sponsored; H-1B transfers and OPT with sufficient time remaining are considered. Flexible arrangements for candidates outside the Bay Area are reviewed case by case.

Requirements

One to five years of full-time experience, including at least one year of full-time work.
Deep experience in at least one of distributed systems, containers and operating-system internals, ML infrastructure, or model training.
Experience training or serving models at real scale, such as distributed training, inference, or serving, or experience building an environment or benchmark behind a published result.
A publication at a top venue, such as ICLR or NeurIPS.
Experience building and owning infrastructure that others depended on, beyond a single research script.
Professional English, as the role involves daily work with technical teams and enterprise customers.
Must be legally authorized to work in the United States. New visa petitions are not sponsored; H-1B transfers and OPT with sufficient time remaining are considered.

Nice To Haves

Experience with checkpointing, cluster orchestration, or scheduling many heterogeneous jobs.
Compiler, inference, or serving work on large models.
Experience with simulation or benchmark environments, such as robotics simulation, agent gyms, browser or operating-system environments, or multi-agent benchmarks.
A master's degree from a strong computer science program.
Interest in joining an early-stage company for the long-term upside.

Responsibilities

Build checkpoint and restore capabilities for full machine state, including memory and GPU state, across many machines.
Build an orchestrator that starts, monitors, and shuts down thousands of environments, ranging from a single container to a multi-GPU cluster.
Provision real cloud accounts for agents, with hundreds created and deleted on demand.
Build realistic simulated companies containing code, people, tickets, threads, and documentation for agent training and evaluation.
Provide the infrastructure foundation on which the research and deployed teams depend.