Senior Scientific Software Engineer — Autoresearch

Bostonfull time

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senior

$160k–$220k

H1B: yes

QuEra Computing Senior Scientific Software Engineer at QuEra Computing to build an autoresearch platform automating theoretical and computational quantum computing research. Develop search and optimization methods and collaborate with researchers to guide exploration and improve software performance.

Responsibilities

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.
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.

Qualification

Strong experimental judgmentLLM-guided searchEvolutionary computationBayesian optimizationInfrastructure for parallel experimentsCompiler optimizationComputational algebraQuantum computing

Required

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

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.

Benefits

Equity/RSU

Company

QuEra Computing

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Source: greenhouse

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