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QuEra Computing

Scientific Software Lead — Infrastructure

Boston, MA, USA; BostonUnited States
Staff · Scientific Software and Compilation
POSTED 1 NOVVERIFIED 3H AGO
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Pay · H-1B filings
$155k
median · n=3 · FY26
Open for
2d
since 1 Nov
H-1B · FY26
6
certified LCAs
Hiring · 30d
71
0 net · open roles
PythonRust

Summary

QuEra Computing is hiring a Scientific Software Lead to manage the Infrastructure team and lead the development of shared programming language, compiler, and runtime foundations for our scientific software stack.

The team builds shared language, compiler, and runtime infrastructure that supports research and engineering across QuEra’s quantum software stack. Its work centers on language design, program semantics, intermediate representations, compiler analyses and transformations, and execution frameworks.

You will combine people management with hands-on technical leadership, working closely with researchers and engineering leads to turn specialized requirements into coherent, reusable infrastructure. The scope may also include tools for automated research and program optimization.

This role suits someone with strong programming languages and compiler expertise who enjoys mentoring engineers, making thoughtful architectural decisions, and supporting teams with different technical needs. Prior quantum computing experience is helpful but not required.

Responsibilities

  • Manage and build the Infrastructure team: hire and mentor engineers, provide clear feedback, and establish priorities that balance foundational work with the needs of partner teams.
  • Lead the team’s technical direction in collaboration with Scientific Software leadership, including language abstractions, intermediate representations, compiler interfaces, and shared execution infrastructure.
  • Guide language and compiler design through explicit semantics, sound reasoning about correctness, and practical implementation; contribute directly to design reviews, code reviews, and critical engineering work.
  • Partner with research and engineering teams to understand their requirements, identify useful shared abstractions, and support adoption through documentation, tooling, and stable interfaces.
  • Own the quality and evolution of the infrastructure, including testing, performance, maintainability, compatibility, and migration planning.

Qualifications

  • Experience managing or leading a technically strong software team, with demonstrated responsibility for mentoring, prioritization, and delivery.
  • Deep practical expertise in compiler engineering and programming language design, including intermediate representations, analyses, transformations, and extensible compiler architectures.
  • Strong grounding in program semantics, type systems, formal methods, or related theory, with the ability to apply that knowledge to concrete engineering decisions.
  • A record of designing and delivering substantial compiler, language, runtime, or developer infrastructure used by other engineers or researchers.
  • Strong software engineering skills and the ability to remain technically engaged through implementation, debugging, and review.
  • Sound judgment in balancing generality, correctness, performance, and delivery, and the communication skills to resolve requirements across teams.

Preferred Qualifications

  • Substantial contributions to well-known open-source compiler, programming language, or runtime projects, such as LLVM/MLIR, Clang, GCC, Rust, CPython, or comparable ecosystems.
  • Extensible compiler frameworks, domain-specific languages, staged programming, or meta-programming.
  • Type systems, program semantics, abstract interpretation, effect systems, or formal verification.
  • Interpreter and virtual machine design, bytecode, runtime interfaces, or deterministic execution.
  • Rust and Python, including infrastructure spanning multiple implementation languages.
  • Compiler testing, differential testing, fuzzing, equivalence checking, or performance benchmarking.
  • Leading shared infrastructure through architectural changes and adoption by multiple teams.
  • Supporting research-oriented development and turning experimental ideas into maintained infrastructure.
  • Automated program synthesis, search-based optimization, or autoresearch systems.
  • Scientific computing, hardware compilation, or quantum software.

We value depth in relevant areas; experience across every topic is not expected. A PhD is welcome but not required.

Source · QuEra ComputingFirst seen 2 NovOriginal ↗