Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI
Communication @ 6
Debugging @ 3
Distributed Systems @ 3
GPU @ 3
LLM
Prioritization @ 6
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
SpaceXAI's RL infrastructure team is looking for an engineer to help develop evaluation infrastructure for next-generation AI models. The role involves building reliable, efficient, and easy-to-use systems for running evaluations at scale and collaborating with modeling and evaluation teams.
Responsibilities
- Build highly reliable, efficient, and easy-to-use infrastructure that runs evaluations at scale.
- Collaborate closely with modeling and evaluation teams to develop new evaluations, maintain evaluation signal quality, and build internal tooling to support training next-generation models.
- Identify and resolve performance bottlenecks across the evaluation infrastructure stack, including inference, capacity fleet management, asynchronous evaluation orchestration, and related systems.
Requirements
Basic Qualifications
- Experience building, debugging, and optimizing large-scale distributed systems.
- Willingness to dive deep and solve difficult problems at all levels of the stack.
Preferred Skills and Experience
- Experience with large language model inference.
- Experience with GPU compute management, workload scheduling, and dynamic resource optimization.
- Experience developing interfaces for comparing models and evaluations.
- Strong communication, prioritization, and problem-solving skills.
Benefits
- Equity.
- Comprehensive medical, vision, and dental coverage.
- Access to a 401(k) retirement plan.
- Short- and long-term disability insurance.
- Life insurance.
- Various other discounts and perks.
- Equal opportunity employer.
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