Research Engineer, Machine Learning
About the role
Basis is a nonprofit applied AI research organization with two goals: understanding and building intelligence, and advancing society's ability to solve complex problems. Research engineers contribute to these goals by developing and refining software that implements the principles of reasoning, learning, decision-making, and understanding.
Responsibilities
- Translate research ideas into correct, robust, and scalable high-quality code.
- Engage in programming language design and implementation.
- Perform performance engineering and scaling research code.
- Develop algorithms and contribute to the culture and direction of Basis.
- (Optional) Publish and present findings in journals and conferences.
Requirements
The ideal candidate possesses excellent programming and software engineering skills, particularly in languages like Julia, Python, C++, and ML-family languages. They should have a strong track record of driving software projects from conception to completion, evidenced by open-source contributions, technical reports, and publications. Comfort with advanced research in programming languages and machine learning is essential, along with the ability to work independently and handle ambiguity.
Significant technical achievements in machine learning engineering are preferred, such as implementing novel techniques, building large-scale model training systems, and contributing to various layers of the software stack. A PhD (or equivalent experience) in technical fields including statistics, programming languages, machine learning, computational neuroscience, cognitive science, physics, or mathematics is advantageous.
Qualifications
While a PhD is preferred, candidates with equivalent experience are encouraged to apply. The role is full-time, with flexible working hours and occasional in-person attendance required for multi-day Basis-wide events. The location is either New York City or Boston, and the compensation range is $120K - $180K.