Overview
The role is ideal for someone with an enterprise development background, strong technology, coding, and data skills, looking to operate in a less constrained environment as part of an accelerated development team.
Responsibilities
Create robust, flexible, and scalable ML tooling and infrastructure to support research scientists leveraging powerful infrastructure such as source control, distributed compute clusters, and data storage. Collaborate as part of a multifunctional team where communication, documentation, and teamwork are highly valued. Write clean, maintainable code, debug complex problems spanning systems, prioritize ruthlessly, and get things done with a high level of efficiency. Coordinate with internal infrastructure and tool teams across the lab and across our client to evaluate and integrate with existing systems. Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving.
Key Skills
* Python, Pytorch, or Tensorflow.
* Deep learning frameworks and large, complex data sets for machine learning, including capture and annotation.
* Experience implementing end‑to‑end prototypical learning systems.
* High performance or distributed compute solutions.
* Deployment and continuous integration experience.
* Machine Learning for audio, multimodal, or DSP purposes.
* Scalable ML tooling/pipelines for researchers.
* Linux or Windows shell scripting.
* Gather requirements and work closely with researchers to develop novel solutions.
* Writing code to support execution of research initiatives.
Experience
Bachelor's degree in computer science or related field, or equivalent work experience. 4+ years industry experience with deep learning frameworks in Python, such as Pytorch or Tensorflow. 2+ years industry experience working with large, complex data sets for machine learning, including capture and annotation.
Top 3 Skills
We're looking for Python and infrastructure focused software engineers with an ML research engineering mindset.
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