AI Inference Core - Infrastructure SW Engineer

Responsibilities

• Design, develop, test, and maintain Python frameworks and services used to orchestrate engineering workflows across machines and clusters.
• Build reusable abstractions for scheduling, distributed execution, resource management, test execution, workflow planning, and failure recovery.
• Define clear APIs, module boundaries, extension points, and data models that allow infrastructure systems to evolve without becoming difficult to maintain.
• Reason about concurrency, asynchronous execution, multiprocessing, state management, retries, idempotency, cancellation, and partial failures.
• Debug complex issues spanning Python applications, operating systems, processes, filesystems, networking, remote machines, and distributed services.
• Write high-quality automated tests and documentation for reliable, widely reused infrastructure.
• Partner with platform, CI, release, quality, ML systems, and product engineering teams to translate requirements into scalable software designs.

Requirements

• 3+ years of professional software-engineering experience.
• Strong proficiency in Python and understanding of its strengths, limitations, and runtime behavior.
• Experience designing maintainable software systems, libraries, frameworks, backend services, or developer-facing APIs.
• Good judgment around software architecture, abstraction boundaries, design patterns, extensibility, and long-term maintainability.
• Understanding of concurrency concepts, including processes, threads, asynchronous execution, synchronization, and shared state.
• Foundational understanding of operating systems, including processes, signals, filesystems, resource management, and program execution.
• Foundational understanding of distributed-systems concepts, including retries, timeouts, idempotency, partial failure, coordination, and eventual consistency.
• Strong debugging and problem-solving skills, including forming hypotheses, gathering evidence, and working independently through unfamiliar systems.

Nice-to-haves

• Experience with Python concurrency technologies such as asyncio, multiprocessing, concurrent.futures, or event-driven systems.
• Experience building orchestration engines, workflow systems, schedulers, distributed job runners, or control-plane software.
• Experience developing test infrastructure or extensions for frameworks such as pytest.
• Familiarity with CI systems, build systems, release infrastructure, or developer-productivity tooling.
• Experience with Kubernetes, containerized environments, cluster schedulers, or remote execution systems.
• BS/MS in Computer Science or a related field, or equivalent practical experience.

Benefits

• Work on a breakthrough AI platform beyond the constraints of GPUs.
• Opportunities to publish and open-source cutting-edge AI research.
• Work on a high-performance AI supercomputer.
• Startup vitality with job stability.
• A non-corporate work culture that respects individual beliefs.
• Continuous learning, growth, and support in an inclusive work environment.