Research Engineer — Collaborative Intelligent Systems

About Basis

Basis is a nonprofit applied AI research organization with two mutually reinforcing goals.

The first is to understand and build intelligence. This entails establishing the mathematical principles of reasoning, learning, decision-making, understanding, and explaining, and constructing software that embodies these principles.

The second is to advance society’s ability to solve intractable problems. This involves expanding the scale, complexity, and breadth of problems we can solve today and, more importantly, accelerating our ability to solve problems in the future.

To achieve these goals, we are building both a new technological foundation inspired by human reasoning, and a new type of collaborative organization that prioritizes human value.

About the Role

Research engineers support Basis’ mission by translating research ideas into correct, robust, and scalable high-quality code.

We seek individuals who excel technically and value probing concepts at their foundations. Our research engineers aspire to conduct rigorous, high-quality, robust science, unafraid to tinker, make mistakes, and explore radically different ideas to achieve this.

Basis is a collaborative endeavor, both internally and with our external partners; we seek individuals who relish working with others on challenges larger than those they can tackle alone.

Research Focus

We study collaborative intelligent systems in the wild, focusing on how social species coordinate, communicate, and adapt in complex environments. Our work spans multiple levels of behavior, from fine-grained group foraging and navigation decisions to city-scale ecological and evolutionary dynamics. Using multimodal data (audio, video, environmental, and genetic), we develop probabilistic and dynamical systems models that investigate how communication and cooperation shape resilience in changing ecosystems. You will contribute to data analysis, modeling, or field data collection for our “behavioral weather station” network monitoring social species across cities.

We expect you to:

  • Possess excellent programming and software engineering skills, especially in Python, Julia, C++, ML-family languages.
  • Have demonstrated the ability to drive software projects from start to finish. This could be evidenced by open-source projects, technical reports, and publications.
  • Be comfortable digesting research from PL and/or ML venues, such as PLDI, POPL, NeurIPS, or ICML.
  • Progress with a high degree of autonomy and under uncertainty.
  • Be enthusiastic about solving real-world problems and making a positive societal impact.
  • Have demonstrated significant technical achievements within ML engineering. Examples include:
    • You’ve implemented variants of newly published techniques from scratch.
    • You build systems and workflows for training large models distributed across many machines.
    • You’ve built systems that span all levels of the programming stack from high-level API infrastructure to close-to-the-metal code.

In addition, experience in the following areas would be an advantage:

  • Building data dashboards
  • Multimodal data infrastructure
  • Data science and data analysis pipelines
  • Data processing and tracking
  • Computer vision/audition

Responsibilities

  • Translate research ideas into correct, robust, and scalable high-quality code.
  • Engage in programming language design/implementation.
  • Performance engineering, scaling research code.
  • Algorithm development.
  • Contribute to the culture and direction of Basis.
  • (Optionally) Publish and present findings in journals and conferences.

Role Details

Exceptional candidates who may not meet all of the following criteria are still encouraged to apply.

  • FT/PT: This is a full-time position
  • In-person Policy: We are in the office four days a week. Be prepared to attend multi-day Basis-wide in-person events.
  • Location: This role is in-person in either Cambridge, MA or New York City.
  • Salary range: Competitive salary

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