SimpliSafe is looking to solve real-world problems in the home security domain by developing and implementing cutting-edge machine learning solutions on embedded devices.
Requirements
- Skilled in C++ and Python
- 3+ years of experience developing vectorized code on ARM using SIMD (Neon, Helium instructions)
- 8+ years of experience in developing production-grade machine learning solutions
- Strong understanding of deep learning architectures and statistical modeling techniques
- Experience with data preprocessing, feature engineering, and model evaluation.
- 3+ years of experience developing and deploying models on edge devices leveraging techniques for quantization such as QAT, PTQ
- Experience with relevant machine learning libraries (e.g., PyTorch TensorFlow, Keras)
Responsibilities
- Support the deployment of ML models and systems on edge devices to solve real-world problems in the home security domain
- Take research initiatives in the embedded ML space from idea generation to production
- Plan, adapt and execute multiple initiatives independently and through others
- Collaborate with engineers and product managers to achieve optimal performance (accuracy vs. power consumption) tradeoff for battery powered devices
- Stay up-to-date on the latest advancements in emerging techniques for model optimization techniques such as compression and quantization
- Contribute to the development of our machine learning infrastructure and tools
- Influence team culture and exemplify best practices in applied research
Other
- Excellent communication and collaboration skills
- Ability to work in a fast paced environment
- Customer Obsessed
- Aim High
- No Ego
