Senior Software Engineer - Decision Science
New
Remote, Candidates can be located anywhere in the United States or Canada.Full-TimeSenior
Salary170,000 - 215,000 USD per year
Apply NowOpens the employer's application page
Job Details
- Experience
- At least 5 years of experience in the field of decision science with a strong software engineering focus, though most great candidates will have closer to 10.
- Required Skills
- PythonMachine LearningNumpyMLOps
Requirements
- At least 5 years of experience in the field of decision science with a strong software engineering focus, 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 decision science 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)
Responsibilities
- Architect, implement, and maintain decision science libraries that will be used in KoBold’s mineral exploration analyses.
- Build tooling to increase the velocity of our decision making, including enabling rapid prototyping in Jupyter notebooks; build experimentation, evaluation, and simulation frameworks; turning successful R&D into robust, scalable pipelines; and organizing ML models and their outputs for repeatability and discoverability.
- 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 decision science technology 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.
View Full Description & ApplyYou'll be redirected to the employer's site
