ML Benchmark Researcher
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IXO Inc.
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Author and validate research-grade machine-learning benchmarks in areas where you write code and publish results.
What you will do- Build realistic research tasks, reference solutions and grading rubrics.
- Validate whether benchmarks measure the intended capability and discriminate between correct and weak approaches.
- Contribute depth in areas such as language models, deep learning, RL, vision/generation, robotics, efficient systems, optimization/theory, classical or adaptive learning, time series, causal reasoning, trustworthy learning or AI for science.
- At least one year of hands-on ML research, with no upper experience limit.
- At least one first-author ML paper or paper in a closely related field.
- Completed or ongoing master’s/doctoral study in a quantitative subject such as machine learning, computer science, statistics or mathematics.
- Practical ML coding in training, evaluation or systems; annotation alone does not meet this research background.
- Multiple first-author papers or results demonstrating measured improvement over a baseline.
- Publications at venues including NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, CoRL or MLSys.
- Deep expertise in an applicable research area.
- Remote work; country restrictions are not stated.
- Flexible remote research work, approximately 5–40 hours per week.
- $158/hr USD hourly compensation. xwjxdcb The applicable rate and agreed work scope are confirmed before work begins.