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Machine Learning Engineer

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Summary

Machine Learning Engineer on Mozee's AI Simulation team builds photorealistic 3D simulation for autonomous vehicles using neural rendering, animation, and scene/object reconstruction. Day-to-day involves Python and PyTorch development, large-scale distributed training on GPU clusters, and generating synthetic data for self-driving models.

Compensation: $125k – $170k

The Role: ML is of critical importance to Mozee's mission. It is safer, makes our rides more enjoyable, and will ultimately deliver on the promise of self-driving robo taxis. As a member of Mozee's AI Simulation team, you will be in a unique position to accelerate the pace at which our AI improves over time. The main ways in which the simulation team realizes this include: Building tools that enable our software developers to perform virtual test drives instead of real ones. Testing all code changes and software releases for regressive behavior. Generating synthetic data sets and reinforcement learning pipelines for neural network training. As an Machine Learning Engineer at mozze, you will contribute to the development of mozze's simulation by enabling and accelerating the creation of photo realistic 3D scenes through neural rendering, neural animation, scene/object reconstruction. More broadly we are looking for experts in these fields: Neural rendering Neural animation Object reconstruction Environment reconstruction Scenario reconstruction Requirements: Expert level Python Skills The team operates in a production setting. An ideal candidate has strong software engineering practices and is 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, MXNet. Some experience with data science tools including Python scripting, numpy, scipy, matplotlib, scikit-learn, jupyter notebooks, bash scripting, Linux environment. About Mozee Mozee is on a mission to develop the first fully autonomous vehicle fleet and the ecosystem needed to bring this technology to market. As a company at the intersection of robotics, machine learning, and design, we aim to provide innovative mobility-as-a-service in urban environments. We are seeking top talent who are passionate about what we do and want to be part of a dynamic and highly-focused team.

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