Advanced Machine Learning Deployment Engineer
7 days ago
About Zendar
Zendar is a pioneering company in software-defined radar technology, developing high-resolution imaging systems for next-generation safety features and driver-assistance technology. Our cutting-edge solutions fuse data streams from multiple sensors to build a more accurate scene and utilize artificial intelligence models that interpret RF spectrum to understand the environment.
Our Technology
We have developed a robust semantic spectrum perception pipeline using millions of training samples, achieving high-performance object detection that positions radar as a key sensor for safety and autonomy in mass-market vehicles. Our models are designed for deployment across diverse edge devices aimed at series production.
Your Role
In this challenging role, you will be a core member of our machine learning and perception team, focusing on optimizing and deploying our machine learning models on targeted edge compute platforms. Key responsibilities include:
- Deeply understanding the capabilities, TOPS, and memory bandwidth of each target platform.
- Designing or adapting models to align with the hardware specifications and supported operations of the edge device.
- Training and testing models to ensure they meet all runtime and performance requirements.
Key Skills
To excel in this role, you will need:
- 3+ years of experience in optimizing deep neural networks and deploying them across diverse compute platforms.
- Proficiency in modern Python and C++.
- Expertise in designing and optimizing neural network models for edge deployment.
- Familiarity with model quantization, quantized aware training, NAS, and model pruning, and other techniques for efficient deployment on edge devices.
- Experience in training, testing, and verifying optimized neural network models.
- Proficient in at least one major deep learning framework (e.g., PyTorch, TensorFlow).
Bonus Points
Award yourself extra points if you have:
- Experience in writing custom CUDA kernels for optimized performance on GPU-based platforms.
- Hands-on experience applying machine learning to perception problems.
- A strong understanding of embedded systems constraints, including power efficiency, memory management, and real-time processing requirements.
- A background in algorithm optimization for resource-constrained environments.
What We Offer
At Zendar, we provide:
- An opportunity to make an impact at a young, venture-backed company in an emerging market.
- A competitive salary ranging from $145,000 to $190,000 annually depending on experience.
- A performance-based bonus.
- Benefits including medical, dental, and vision insurance, 401(k) plan, flexible PTO, and equity.
- Daily catered lunch and a stocked fridge when working in our Berkeley, CA office.
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