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Senior Software Engineer, Scientific Computing

KoBold Metals

Remote · location unlistedFull-time$170–215K/yrPosted 11mo agoStill listed 3 days ago

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At a glance

Compensation
$170–215K/yr
Location
Remote · location unlisted
Schedule
Full-time
Work Authorization
US work authorization required

Olive lists jobs from US employers, including remote roles you can work from the United States.

Job overview

KoBold Metals is hiring a Senior Software Engineer, Scientific Computing. Senior Software Engineer, Scientific Computing at KoBold Metals will apply software engineering and machine learning to mineral exploration data, building scalable ML systems and scientific computing tools while collaborating with data scientists and geologists to accelerate discovery and support sustainable energy transition.

Key focus areas include Architect, implement, and maintain foundational scientific computing libraries for mineral exploration analyses, Build tooling to increase machine learning progress, including rapid prototyping, experimentation, evaluation, and simulation frameworks, and Build models to make statistically valid predictions of ore metal locations.

Successful candidates bring 5+ Years As Software Engineer, 5+ Years As Data Scientist, and 5+ Years As ML Engineer. Important skills include Architect Scientific Computing Libraries, Implement Scientific Computing Libraries, Maintain Scientific Computing Libraries, Build Tooling For ML Progress, Rapid Prototyping In Jupyter Notebooks, and Build Experimentation Frameworks.

Skills & qualifications

RequiredNice to have

Skills

Architect Scientific Computing LibrariesImplement Scientific Computing LibrariesMaintain Scientific Computing LibrariesBuild Tooling for ML ProgressRapid Prototyping in Jupyter NotebooksBuild Experimentation FrameworksBuild Evaluation FrameworksBuild Simulation FrameworksBuild Scalable ML PipelinesOrganizing Models for RepeatabilityOrganizing Models for DiscoverabilityBuild Models for Statistical PredictionsEngineering Best PracticesWriting Robust CodeWriting Testable CodeWriting Composable CodeCollaborate With Data ScientistsCollaborate With GeoscientistsCollaborate With EngineersInvent Modern Scientific Computing StackBuilding Production Quality Data Processing SolutionsBuilding Tooling Delivering Business ValueFoundational Concepts of MLStatistical ApproachesTraditional ML ApproachesDeep-Learning ApproachesPythonMeasured Scientific DataVisualizing Scientific Data for Domain ExpertsMLOpsMaking Robust ML SystemsIncrease Velocity of Data ScientistsIncrease Effectiveness of Data ScientistsUnderstanding GeologyUnderstanding Mineral Exploration PracticesWorking With Limited Data SourcesWorking With Disparate Data SourcesWorking With Noisy Data SourcesCollaborative AttitudeTake Ownership of Large ProjectsTake Responsibility of Large ProjectsIntellectual CuriosityEagerness to Learn About Mineral ExplorationOpen to Working Directly With Geologists in the FieldConstantly LearningDriving InsightsDriving InnovationsExplain Technical Problems to Domain ExpertsCollaborate on Solutions With Domain ExpertsStrong Communication

Qualifications

5+ Years as Software Engineer5+ Years as Data Scientist5+ Years as ML EngineerLegally Authorized to Work in the United States

Full job description

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. In the six years since founding, 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.

  • 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.

  • In collaboration with data scientists, build models to make statistically valid predictions about the locations of economic concentrations of ore metals within the Earth’s crust.

  • 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.

  • 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

  • Deep experience with measured scientific data

  • Experience in visualizing scientific data for domain experts

  • Experience in MLops and in the making of robust ML 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 ML 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.

What to Expect

Joining KoBold means getting the opportunity for hands-on exposure to our exploration projects around the world. All employees are expected to travel to project sites, with a minimum of one week per year. Field-facing and technical roles spend significantly more time in the field.

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

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