As a member of the Avala AI team you will research, design, implement, optimize and deploy deep learning models that advance the state of the art in perception for various computer vision and general purpose AI applications. A typical day to day includes reading deep learning code/papers, implementing described models and algorithms, adapting them to our setting, driving up internal metrics, working with downstream engineers to integrate neural networks to run efficiently.
We are looking for an experienced Machine Learning Scientist/Engineer. This is an opportunity to have a big impact and get lots of ownership. We're looking for someone who thrives in the very early stages of a company and is self driven.
You'll enjoy this role if you can
- Train machine learning and deep learning models on a computing cluster to perform visual recognition tasks, such as segmentation and detection
- Develop state-of-the-art algorithms in one or all of the following areas: deep learning (convolutional neural networks), object detection/classification, tracking, multi-task learning, large-scale distributed training, multi-sensor fusion, etc.
- Optimize deep neural networks and the associated preprocessing/postprocessing code to run efficiently on mobile devices
- Shaping our practice as one of our early hires, bringing your technical leadership, experience, and knowledge of best practices to establish a strong engineering culture.
- Strong software engineering foundations and a desire to apply those skills toward making other engineers more productive
- Very comfortable with Python programming, debugging/profiling, and version control.
- We train neural networks on a cluster in large-scale distributed settings. An ideal candidate is very comfortable in cluster environments and understands the related computer systems concepts (CPU/GPU interactions/transfers, latency/throughput bottlenecks during training of neural networks, CUDA, pipelining/multiprocessing, etc).
- We are at the cutting edge of deep learning applications. The ideal candidate has a strong understanding of the under the hood fundamentals of deep learning (layer details, backpropagation, etc). Additional requirements include the ability to read and implement related academic literature and experience in applying state of the art deep learning models to computer vision (e.g. segmentation, detection) or a closely related area (speech, NLP).
- Experience with PyTorch, or at least another major deep learning framework such as TensorFlow, Darknet, MXNet.
- Experience with data science tools including Python scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks, bash scripting
- Must be willing to constantly learn new things.
- Passionate about joining a small team and building a company.
Nice To Have Skills
- You've worked at a startup before.
- You've shipped production AI applications before.
- A history of working on side/hobby projects and contributing to open source projects is a plus.
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