Senior Scientific Software Engineer — Autoresearch
About The Position
QuEra Computing is hiring a Senior Scientific Software Engineer to build systems that automate theoretical and computational research in quantum computing. The role 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 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. The engineer will combine classical search and optimization with AI agents and develop methods that progressively improve the research process itself. QuEra welcomes experienced engineers and researchers, including recent PhD graduates with substantial implementation ownership; a PhD is welcome but not required.
Requirements
- Strong software engineering skills and a record of independently delivering substantial research or developer tools.
- 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, including 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.
Nice To Haves
- 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.
- A PhD is welcome but not required; recent PhD graduates with substantial implementation ownership are welcome.
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.
Benefits
- Equity grants for all new hires.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
