Autoresearch Platform Engineer - Quantum & AI

QuEra Computing, Inc.; Boston (MA); Presencial; USD 102.000 - 166.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Equity grants

Descripción de la vacante

QuEra Computing, Inc. is hiring a Senior Scientific Software Engineer to build systems that automate theoretical and computational research in quantum computing.

You will develop a reusable autoresearch platform that generates hypotheses, implements and evaluates candidates, and uses accumulated evidence to guide exploration. This is a hands-on engineering role with substantial technical ownership, combining classical search, AI agents, and methods to improve the research process itself.

Formación

• Strong software engineering skills and a track record of delivering substantial research or developer tools.
• Proficiency in Rust or a comparable systems language and scientific programming in Python.
• Experience in search and optimization, including combinatorial optimization or meta-heuristics.
• Hands-on experience building automated discovery or optimization systems.

Responsabilidades

• Design and build the autoresearch platform with programmable search strategies and long-running experiments.
• Develop and evaluate search and optimization methods for generating, selecting, refining, and combining candidates within budgets.
• Collaborate with theorists and compiler researchers to translate questions into search spaces and executable procedures.
• Establish reproducible evidence of progress with baselines, noise-aware measurement, and independent validation.

Conocimientos

Rust

Python

Software engineering

Search and optimization

Experimental judgment

Educación

PhD welcome but not required

Descripción del empleo

QuEra Computing, Inc. is hiring a Senior Scientific Software Engineer to build systems that automate theoretical and computational research in quantum computing.

You will develop a reusable autoresearch platform that generates hypotheses, implements and evaluates candidates, and uses accumulated evidence to guide exploration. This is a hands-on engineering role with substantial technical ownership, combining classical search, AI agents, and methods to improve the research process itself.