Staff Machine Learning Engineer


Engineering & Technology

IT & Telecoms Confidential
2 months ago

Job Summary

We’re building a next-generation creative tool that enables a new level of interactivity with cloud-based machine learning models. For our tool to be maximally expressive, we’re working to establish a seamless feedback loop between our users and the machine learning models powering Runway’s abilities. It’s not sufficient for our models to be accurate; nor is it enough for our user interface to be beautiful and responsive; we need to ensure that the link between the two is as fast and reliable as possible. For this reason, we’re looking for a Machine Learning Engineer who can help us create the server-side engine that powers our interactive tools for image and video synthesis. You’ll be working closely with our research and frontend teams to design and build low-latency, high-reliability machine learning deployments. We’re looking for someone who is deeply interested in the intersection of machine learning and systems design, and has extensive experience building web-based real-time server applications.

  • Minimum Qualification: Degree
  • Experience Level: Senior level
  • Experience Length: 5 years

Job Description/Requirements

What you’ll do 

  • Work with a world-class engineering team pushing the boundaries of content creation on the browser
  • Collaborate with our research team to deploy state-of-the-art computer vision models to production
  • Improve the performance and efficiency of our machine learning deployments

What you’ll need 

  • Solid knowledge of at least one machine learning research framework (e.g. PyTorch, Tensorflow), and at least one high-performance inference framework (e.g. TensorRT, Apache TVM)
  • Experience profiling and optimizing deep neural networks, including knowledge of GPU profiling tools such as NVIDIA Nsight
  • Familiarity with Python-based image and video manipulation/encoding/decoding frameworks, such as OpenCV and PyAV
  • Experience with cloud orchestration systems such as Kubernetes and cloud providers such as AWS, GCP, and Azure
  • Ability to write robust and maintainable client-server architectures and APIs
  • Ability to rapidly prototype solutions and iterate on them with tight product deadlines
  • Strong communication, collaboration, and documentation skills

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