Machine Learning Architect
3 weeks ago
Zendar is a pioneering company in software-defined radar technology, fusing data streams from multiple sensors to build a more accurate scene. Our team has 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.
Job Summary
In this role, you will be a core member of the 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.
Requirements
• 3+ years of experience in optimizing deep neural networks and deploying them across diverse compute platforms.
• Proficiency in modern Python and C++ programming languages.
• Expertise in designing and optimizing neural network models for edge deployment.
• Familiarity with model quantization, quantized aware training, NAS, and model pruning 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).
• Strong communication skills and proven ability to collaborate effectively across functions.
What We Offer
• Competitive salary ranging from $145-190k annually depending on experience.
• Performance-based bonus.
• Benefits including medical, dental, and vision insurance, 401k plan, flexible PTO, and equity.
• Opportunity to make an impact at a young, venture-backed company in an emerging market.
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