Senior Software Engineer, Scientific Computing (Hardware/Sensors)
矿业行业在寻找新矿石矿产方面不断恶化,需要超过10倍的资金来进行发现。相比30年前,容易找到的近表面矿产已很大程度上被发现,并且该行业一直不充分投资于新的勘探技术,依赖过去的手动技术,即使需求加速为建造电动汽车,可再生能源和数据中心的铜,和其他金属。科博尔德为矿物勘探开发公司构建 AI 模型,并与我们的新型传感器一起部署这些模型来指导科博尔特拥有和运营的勘探计划的决策。自2018年成立以来,科博尔兹已成为最大的独立矿物勘测公司和最大的勘探技术开发商。来自领先的科技公司的数据科学家和软件工程师们与我们知名的勘探地质学家共同领导了勘探项目。科博尔已经证明其首次发现资金比行业平均水平少得多,并且发现了迄今为止最好的铜矿产之一:铜矿的总量远高于全球平均水平,仅此资产预计将在几十年内产生有意义的收入。科博尔德拥有60多个项目组合,其中每个项目都有另一个高质量的发现潜力。科博爾德是私人公司;投资者包括机构资产管理员 T.罗威普莱斯和加拿大养老金计划投资;技术风险投资者安德烈森·霍洛维茨,突破能源风险投注,BOND 资本,可持续资本,StepStone 和标准投资;以及自然资源公司 Equinor,BHP 和三。关于角色 在 KoBold,我们相信现代科学计算堆将使矿物勘探系统化并显著提高我们的矿物发现率。这个角色是这一战略的关键成分。作为我们的科学计算机团队成员,你将应用软件工程和机器学习到远程传感,钻孔,成像,地质物理和其他矿物勘测数据以建立可扩展的 ML 系统来帮助为我们的矿物勘验项目做出高速高品质决策。与我们的特殊数据科学家和地质学家团队合作,你将面对复杂的科学问题,共同开辟道路,
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Senior Software Engineer, Scientific Computing
About the Company
The mining industry has steadily become worse at finding new ore deposits, requiring >10X more capital to make discoveries compared to 30 years ago. The easy-to-find, near-surface deposits have largely been found, and the industry has chronically under-invested in new exploration technology, relying on the manual techniques of yesteryear – even as demand accelerates for copper, lithium, and other metals to build electric vehicles, renewable energy, and data centers.
KoBold builds AI models for mineral exploration and deploys those models—alongside our novel sensors—to guide decisions on KoBold-owned-and-operated exploration programs. Since our founding in 2018, KoBold has become by far both the largest independent mineral exploration company and the largest exploration technology developer. Our data scientists and software engineers, who come from leading technology companies, jointly lead exploration programs with our renowned exploration geologists.
KoBold has proven its first discovery with materially less capital than the industry average and found one of the best copper deposits ever discovered: the copper is far more concentrated than the global average of copper mines, and this asset alone is expected to generate meaningful revenue for decades. KoBold has a portfolio of more than 60 other projects, each of which has the potential for another high-quality discovery.
KoBold is privately held; investors include institutional asset managers T. Rowe Price and Canada Pension Plan Investments; technology venture capitalists Andreessen Horowitz, Breakthrough Energy Ventures, BOND Capital, Durable Capital, StepStone, and Standard Investments; and natural resources companies Equinor, BHP, and Mitsubishi.
About the Role
At KoBold we believe that a modern scientific computing stack will enable systematic mineral exploration and materially improve our rate of mineral discovery. This role is a key ingredient to this strategy. As a member of our scientific computing team, you will apply software engineering and machine learning to remote-sensing, drillhole, imaging, geophysics and other mineral exploration data in order to build scalable ML systems to help make high-speed, high-quality decisions for our mineral exploration projects. Collaborating with our exceptional team of data scientists and geologists, you will tackle complex scientific problems head-on and collectively pave the way for discoveries of vital energy transition metals like lithium, copper, nickel, and cobalt. Together we can shape the future of mineral exploration and contribute to building a sustainable world.
Responsibilities
- Architect, implement, and maintain foundational scientific computing libraries that will be used in KoBold’s mineral exploration analyses.
- Integrate third-party and domain-specific tooling — code you did not build and cannot modify — into a coherent, repeatable pipeline: getting a heterogeneous stack to exchange data and behave correctly.
- Build tooling to increase the velocity of our machine learning progress, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable ML pipelines; and organizing models and their outputs for repeatability and discoverability.
- Debug across boundaries — third-party binaries, undocumented formats, other people's code, and deployed instrumentation — rather than escalating at the edge of your own module.
- Apply–and coach team members to use–engineering best practices such as writing robust, testable and composable code.
- Collaborate with data scientists, geoscientists and engineers to invent the modern scientific computing stack for mineral exploration.
- Occasional travel to exploration sites around the world to observe the impact of scientific computing on KoBold’s exploration products and design new technologies to further discovery. Travel is approximately twice per year depending on project needs.
Qualifications
Our ideal candidate will have:
- At least 5 years of experience as a software engineer, data scientist or ML engineer, though most great candidates will have closer to 10.
- Work experience across many distinct technical problem types.
- Track record of building production quality data processing solutions or tooling that have delivered business value
- Proficiency with foundational concepts of ML, including statistical, traditional and deep-learning approaches.
- Proficiency in Python, ideally including array-based packages such as xarray and numpy.
- Experience with data that comes from the physical world: physical measurements, scientific instrument output, imagery, or geophysical data.
- Experience in visualizing scientific data for domain experts.
- Hands-on history with hardware, flight, space, lab instrumentation, or field-deployed systems.
- Drive to increase the velocity and effectiveness of our data scientists in both experimental and production workflows.
- Capacity to dive deep on novel challenging problems in applying new technologies to mineral exploration, including understanding a complex domain of geology and mineral exploration practices as well as working with limited, disparate and noisy data sources.
- Collaborative attitude to work with stakeholders with different backgrounds (data scientists, geoscientists, software engineers, operations).
Work practices and motivation:
- Ability to take ownership and responsibility of large projects.
- Intellectual curiosity and eagerness to learn about all aspects of mineral exploration, particularly in the geology domain. Open to working directly with geologists in the field. Enjoys constantly learning such that you are driving insights and innovations.
- Ability to explain technical problems to and collaborate on solutions with domain experts who aren’t software developers. A strong communicator who enjoys working with colleagues across the company.
- Excitement about joining a fast-growing early-stage company, comfort with a dynamic work environment, and eagerness to take on a range of responsibilities.
- Keen not just to build cool technology, but to figure out what technical product to build to best achieve the business objectives of the company.
- Ability to independently prioritize multiple tasks effectively.
KoBold Metals is an equal opportunity workplace and an affirmative action employer. We are committed to equal employment opportunity for people of any race, color, ancestry, religion, sex, gender identity, sexual orientation, marital status, national origin, age, citizenship, disability, or veteran status.
This position is Full-time
The US base salary range for this full-time exempt position is $170,000 - $215,000
Location: Remote, Candidates can be located anywhere in the United States or Canada. All candidates must be legally authorized to work in the United States or Canada.
Originally posted on Himalayas