Senior Research Infrastructure Engineer (AI)

Location: On-site in San Francisco or Singapore, or remote from Asia, North America, and the rest of the world with 70-80% working-hours overlap with San Francisco or Singapore time zones. Relocation and visa support is available for strong full-time candidates moving to the US or Singapore.

Base salary: $175,000-$260,000 in San Francisco and other major US cities; $130,000-$195,000 in Singapore; $105,000-$195,000 in the rest of the world. Offers are adjusted for experience and location.

Company

hirify.global builds infrastructure for AI data, including a marketplace and platform used by startups, Fortune 500 companies, and frontier labs.

What you will do

• Build reliable infrastructure for agent-behavior research, including environment execution, trajectory collection, and evaluation at scale.
• Develop reusable tools, APIs, and pipelines for launching experiments, managing datasets and configurations, and inspecting trajectories and evaluation results.
• Turn research prototypes and experimental workflows into tested, documented, reusable software.
• Design experiments to investigate model behavior, agent failure modes, and data quality issues.
• Improve orchestration, observability, recovery from failed runs, experimentation speed, reproducibility, and cost efficiency.
• Partner with research and engineering to translate evolving research needs into infrastructure priorities and architecture decisions, owning systems through ongoing operation.

Requirements

• Strong software engineering fundamentals and proficiency in Python, with experience building maintainable systems used by others.
• Experience owning backend services, data pipelines, developer tools, or infrastructure from design through deployment and operation.
• Sound judgment regarding APIs, data models, asynchronous workloads, and reliability tradeoffs.
• Comfort with Docker, Linux, cloud infrastructure, and debugging failures across application code and the systems it runs on.
• Ability to work closely with researchers, understand experimental workflows, and translate open-ended research needs into useful software.
• Independent technical judgment for setting priorities, making pragmatic architecture decisions, and improving systems as users and workloads grow.

Nice to have

• Working knowledge of reinforcement learning, including environments, rollouts, reward signals, and evaluation workflows.
• Experience building research infrastructure, ML pipelines, or tools that increased research-team velocity.
• Familiarity with distributed job execution, containerized environments, or high-concurrency workloads.
• Experience improving experiment reproducibility, data lineage, or visibility into complex pipeline failures.

Culture & Benefits

• Full-time role with a rapidly scaling team of researchers, engineers, and operators; most employees work in person, with remote options.
• 100% covered medical, dental, and vision insurance for US and Singapore employees.
• Lunch and dinner for in-office employees, PTO, paid holidays, and a company-wide holiday break from Christmas Eve through New Year's Day.
• 401(k) with a 4% match, commuter benefits for US employees, and a health and wellness stipend for Singapore employees.
• Access to AI development tools, an annual travel budget to visit either office, and additional location-specific perks.

Hiring process

• Applications are reviewed on a rolling basis.
• The process includes two technical interviews followed by a 2-3 day work trial.
• Technical aptitude and learning potential are prioritized over years of experience.