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KoBold

Senior Software Engineer, Scientific Computing (Hardware/Sensors)

УдалённоUnited States, Canada только
Опубликовано
Роль
Инженерия данных
Опыт
Синьор
Занятость
Полная занятость
Размер компании
Средняя
$170k–$215k/yr
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Доступно для: US, CA only. Укажите, откуда вы работаете, чтобы проверить доступность.

Коротко по делу

Senior software engineer for scientific computing focused on hardware/sensors and remote-sensing/drillhole/geophysical data. Requires strong Python (numpy/xarray), ML foundations, production data-processing tooling, and experience with physical/scientific instrumentation. Remote in US or Canada; must be legally authorized to work in the US or Canada.

Ключевые навыки

Pythonxarray

Обязательные навыки

NumPymachine learningdata processingdata visualizationdebugging across binaries/formatsexperiment/iteration toolingML pipelines

Желательные навыки

deep-learningstatistical ML methodsexperience with flight/space/lab/field instrumentationremote-sensinggeophysical dataimaging

Чем предстоит заниматься

  • Architect, implement, and maintain foundational scientific computing libraries for mineral exploration analyses.
  • Integrate third-party and domain-specific tooling into coherent, repeatable pipelines.
  • Build tooling for rapid prototyping in Jupyter notebooks, experimentation, evaluation, and simulation frameworks.
  • Turn successful R&D into robust, scalable ML pipelines and organize models/outputs for repeatability and discoverability.
  • Debug across boundaries including third-party binaries, undocumented formats, other people's code, and deployed instrumentation.
  • Apply and coach engineering best practices: robust, testable, composable code.
  • Collaborate with data scientists, geoscientists and engineers to invent the scientific computing stack.
  • Occasional travel (~twice per year) to exploration sites to observe impact and design new technologies.

Что требуется

  • At least 5 years of experience as a software engineer, data scientist or ML engineer (many candidates closer to 10).
  • Work experience across many distinct technical problem types.
  • Track record of building production-quality data processing solutions or tooling that delivered business value.
  • Proficiency with foundational ML concepts including statistical, traditional and deep-learning approaches.
  • Proficiency in Python, ideally including array-based packages such as xarray and numpy.
  • Experience with data from the physical world: physical measurements, scientific instrument output, imagery, or geophysical data.
  • Experience visualizing scientific data for domain experts.
  • Hands-on history with hardware, flight, space, lab instrumentation, or field-deployed systems.
  • Drive to increase velocity and effectiveness of data scientists in experimental and production workflows.
  • Capacity to dive deep on novel challenging problems and work with limited, disparate and noisy data sources.
  • Collaborative attitude to work with stakeholders from different backgrounds.
  • Ability to take ownership of large projects and strong communication skills.
  • Excitement about working at a fast-growing early-stage company and comfort with a dynamic environment.

Преимущества

  • Equal opportunity / affirmative action employer statement

KoBold builds AI models for mineral exploration and deploys those models—alongside novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs.

MiningСредняя
$170k–$215k/yr