Senior Scientific Software Engineer - Autoresearch

Summary

QuEra Computing 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 further exploration. Initial applications include automated performance improvement across our software repositories, quantum-error-correction code discovery with QEC theorists, and architecture search with compiler researchers.

This is a hands-on engineering role with substantial technical ownership. You will combine classical search and optimization with AI agents, and develop methods that progressively improve the research process itself.

Responsibilities

• Design and build the autoresearch platform, including programmable search strategies, agent and tool integration, and reliable execution of long-running experiments.
• Develop and evaluate search and optimization methods for generating, selecting, refining, and combining candidates under limited computational budgets.
• Collaborate with theorists and compiler researchers to translate research questions into search spaces, constraints, objectives, and executable evaluation procedures.
• Establish reproducible evidence of progress through correctness checks, strong baselines, noise-aware measurement, and independent validation; deliver useful discoveries and software improvements.

Qualifications

• Strong software engineering skills and a record of independently delivering substantial research or developer tools, with proficiency in Rust or a comparable systems language and scientific programming in Python.
• Deep practical experience in search and optimization, particularly combinatorial optimization, evolutionary algorithms, meta-heuristics, or automated algorithm design.
• Hands-on experience building automated discovery or optimization systems that iteratively generate candidates, execute experiments, and learn from feedback.
• Strong experimental judgment: choosing meaningful objectives, allocating evaluation budgets, diagnosing failures, and distinguishing genuine improvements from noise or evaluation artifacts.
• Ability to work with researchers across disciplines and turn mathematical ideas into reliable computational tools.

Preferred Qualifications

• LLM-guided search, automated algorithm design, program synthesis, or autonomous research systems.
• Evolutionary computation, quality-diversity methods, tree search, hyper-heuristics, or adaptive selection of search operators.
• Bayesian optimization, bandit methods, experimental design, or other approaches to allocating expensive evaluation budgets.
• Performance engineering and automated software tuning, including profiling, benchmarking, and statistical treatment of measurement noise.
• Infrastructure for parallel experiments, isolated execution, checkpointing, and reproducible tracking of candidates and results.
• Compiler optimization, scheduling, routing, or hardware-software architecture search.
• Computational algebra, constraint solving, theorem proving, or formal verification.
• Quantum computing, quantum error correction, fault-tolerant architectures, or quantum simulation.
• Systems that improve their own search strategies, tools, or experimental workflows and reuse findings across tasks.

• We value depth in relevant areas; experience across every topic is not expected.
• We welcome experienced engineers and researchers, including recent PhD graduates with substantial implementation ownership. A PhD is welcome but not required.

Pay and benefits

The approximate base salary range for this position is $160,400 - $220,400.

We consistently monitor external market data and update base salary ranges accordingly. We determine base compensation decisions on several factors, including as geographic placement, role-specific knowledge, skills, and/or experience. In addition to our base salary offerings, we also provide equity grants for all new hires.

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