Research Engineer — Machine Learning

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.

Machine Learning Research Engineers

This role targets experts in machine learning engineering. The core areas of ML research engineering include:

• Probabilistic programming and statistical inference
• Deep learning
• Causal inference
• ML Ops and systems engineering

These areas are honed within the context of building reasoning systems. Consequently, research engineers will also engage with topics such as automatic differentiation and the intersection of learning and reasoning.

We expect you to:

• Possess excellent programming and software engineering skills, especially in Julia, Python, 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 ML venues, such as 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, the following would be an advantage:

• A PhD (or equivalent experience) in technical areas including: statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, mathematics.

Responsibilities:

• Translate research ideas into correct, robust, and scalable high-quality code.
• 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

• 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 New York City or Cambridge, MA.
• Salary range: Competitive salary

Not sure you meet every detail? Whether it’s qualifications, work pattern, or location, exceptional candidates who don’t check every box above are still encouraged to apply.

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