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Research Engineer
Full-Time · San Francisco
Apply ↓You will be working on Conway's core discovery technology. You will focus on building out "detectors" that find statistically significant structures in arbitrary data — principally high-dimensional semantic and numeric data. In your role, you will be responsible for building, proving, and evaluating every improvement you derive.
Sample projects include:
- • Building an information-theoretic eval suite to determine how well our detectors capture 'unknown unknowns'
- • Research and formalize novel dimensionality reduction techniques to allow for tractable inference in high dimensional data
- • Train and test transformer-based anomaly detection algorithms
Requirements:
- • Formal training in statistics, mathematics, and/or physics. To succeed in this role, you will need a mastery of a graduate mathematics or statistics curriculum or an equivalent research experience
- • Some production engineering experience (e.g. ML in an applied setting). No spaghetti research code
Nice to haves:
- • 1+ years of experience at a quant shop, particularly working as a quantitative researcher
- • First-author publications in top-tier ML conferences (NeurIPS, ICML, ICLR, and others)