Staff Data Scientist
About Redwood Materials
Staff Data Scientist
Redwood Materials is looking for talented data scientists and machine learning engineers to work on several special projects which involve making real world inferences based on complex sensor and imagery data. Some examples of this data are x-ray scans, 3d imaging, and spectrometry data. This role will require creativity, thoughtfulness, and engineering intuition to extract features and build models that identify and predict physical phenomena.
This is an opportunity to join during a critical growth phase and build green field software which is critical to the technical growth and scaling of the company.
Responsibilities will include:
- Leading technical teams, managing project requirements and timelines
- Deploying machine learning/data pipelines to cloud infrastructure
- Designing robust cloud architecture for machine learning projects
- Utilizing your experience in a physical engineering discipline, physics, or strong intuition around modeling mechanical/electrical/chemical/high-energy radiation processes
- Bachelor’s degree in Computer Science, an Engineering discipline, or equivalent practical experience.
- Strong software architecture and coding skills. We are looking for folks capable of developing and deploying pipelines and writing clean, maintainable code, much of which will be used in production.
- 5 years of in-depth experience working with classical machine learning methods (trees, clustering, SVM, ability to blend techniques and pick the right tool for the job), 4 years of professional software development experience.
- Ability to implement algorithmic machine learning-esque models for problems that are not solved well by standard/textbook machine learning techniques.
- Strong experience with Python, Pandas, scikit-learn, relational databases, Linux, working in cloud environments.
The position can be remote with occasional travel or in-person at our headquarters in Carson City, Nevada.
The position is full-time. Compensation will be commensurate with experience.
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