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Senior Applied Scientist, ML DSP
1 month ago
Gridware is a pioneering company that aims to enhance and protect the electrical grid, a critical infrastructure that underpins modern society. Our team of experts engineers advanced sensing systems to analyze the electrical and mechanical behavior of grid assets, identifying potential faults and enabling preemptive mitigation. This technology has been proven to bolster safety, reliability, and reduce customer outage durations.
We are seeking a Senior Applied Scientist specializing in Machine Learning with Digital Signal Processing to join our team. The ideal candidate will possess deep knowledge of machine learning architectures, digital signal processing techniques, and algorithm design.
Key Responsibilities:
- Develop and evaluate models for multimodal time series sensor data on resource-constrained computation systems.
- Design and build physically-informed data augmentation and domain randomization algorithms.
- Conduct literature reviews and research on resource-constrained inference and training techniques.
- Collaborate with cross-functional teams, including hardware engineers, firmware engineers, and product managers.
Requirements:
- Computer Science or Electrical Engineering degree.
- 4+ years of professional experience with production machine learning models.
- 4+ years of professional experience with physical sensors and time series data modeling.
- 4+ years of research experience.
- Experience with low-level languages and memory management.
- Strong fundamentals in statistics and computer science.
We offer a competitive compensation package, including flexible hours, health insurance, paid parental leave, and commuter allowance. Gridware is an equal opportunity employer and welcomes applicants from diverse backgrounds.
