Senior Software Engineer - Scientific Computing
New
K
KoBold MetalsMining, Mineral Exploration
Remote, Candidates can be located anywhere in the United States or Canada.Full-TimeSenior
Salary170,000 - 215,000 USD per year
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Job Details
- Experience
- At least 5 years of experience
- Required Skills
- PythonMachine LearningNumpyData visualizationMLOps
Requirements
- At least 5 years of experience as a software engineer, data scientist, or ML engineer.
- Track record of building production-quality data processing solutions or tooling that delivered business value.
- Proficiency with foundational machine learning concepts including statistical, traditional, and deep-learning approaches.
- Proficiency in Python, 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 building robust ML systems.
- Ability to work with complex, limited, disparate, and noisy data sources.
- Collaborative attitude to work with diverse stakeholders including data scientists, geoscientists, and operations.
- Strong communication skills with the ability to explain technical problems to domain experts.
- Capacity to independently prioritize multiple tasks and take ownership of large projects.
Responsibilities
- Architect, implement, and maintain foundational scientific computing libraries for mineral exploration analyses.
- Build tooling to increase the velocity of machine learning progress, including experimentation and simulation frameworks.
- Turn successful R&D into robust, scalable ML pipelines.
- Collaborate with data scientists to build models making statistically valid predictions for economic mineral concentrations.
- Apply and coach team members on engineering best practices including robust, testable, and composable code.
- Collaborate with cross-functional teams to invent the modern scientific computing stack for mineral exploration.
- Travel to exploration sites worldwide approximately twice per year to observe technology impact and design new discovery tools.
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