The Data Science Institute is looking for a Staff Associate III (Research Software Engineer) eager to work in an academic environment towards this goal, at the cutting edge of probabilistic programming, causal inference, program synthesis and machine learning. Specifically, this role is to develop and engineer algorithms, languages and systems for causal probabilistic programming.
You'll be working broadly with members of the DSI and largely with Associate Research Scientist Zenna Tavares; you can see the kind of work he does at his website zenna.org.
You will be focused on developing systems for automatic causal and probabilistic inference, in an emerging area called causal probabilistic programming. The goal is to build systems that can reason coherently about the real world, in all of its complexity and ambiguity. These systems should allow data scientists to build sophisticated models of the world, determine causal effects, design experiments and interventions, and ultimately construct explanations. On this foundation we are building AI systems that are trustworthy, with an immediate focus on causal interpretations of algorithmic fairness.
We are eager for not only passionate software engineers, but especially those with interest and expertise with some subset of the following academic areas:
Bayesian modeling and inference
Modern (deep) machine learning
Compilers design and engineering
Program analysis and verification
Automated / interactive theorem proving
Strong coding skills in multiple programming languages, especially Julia, but also
Python, C++, ML-family.
Comfortable with digesting academic research papers from venues like OOPSLA,
PLDI, POPL, ICSE/FSE, and/or NeurIPS, ICLR or ICML. Having published work in
these venues is a bonus.
Columbia University is an Equal Opportunity Employer / Disability / Veteran
Columbia University is one of the world's most important centers of research and at the same time a distinctive and distinguished learning environment for undergraduates and graduate students in many scholarly and professional fields. The University recognizes the importance of its location in New York City and seeks to link its research and teaching to the vast resources of a great metropolis. It seeks to attract a diverse and international faculty and student body, to support research and teaching on global issues, and to create academic relationships with many countries and regions. It expects all areas of the university to advance knowledge and learning at the highest level and to convey the products of its efforts to the world.