Zencastr

Zencastr

Senior Machine Learning Engineer (Remote)

New York Office · Senior

Sponsorship not specifiedDetected 348 days ago
PythonAlgorithmsSQLMongoDBAWSGCPDockerKubernetesMachine LearningTensorFlowPyTorchscikit-learnSignal ProcessingLoad TestingResearchMentoring

About the role

  • We are looking for an outstanding machine learning engineer to join our team!
  • The role will provide an opportunity to work on large scale machine learning to improve the podcast creation experience at Zencastr.
  • Work with some of the brightest minds in signal processing

Responsibilities

  • Collaborate with engineering partners and colleagues in large multi-functional efforts to build new product features that advise and enrich Zencastr's various ML services.
  • Drive forward audio and text capabilities within the ML team

Requirements

  • 5 + years experience in Python
  • 3+ years experience training or deploying neural networks
  • Experience with building and operating production-ready ML systems
  • Experience with cloud technologies (Google Cloud, AWS, Modal)
  • You are able to succeed with minimal mentorship and process.

Nice to have

  • Publications in peer-reviewed journals from a related field
  • Experience with modern speech processing frameworks
  • Good dev ops experience
  • Advanced DSP experience
  • MongoDB or SQL experience
  • Experience with unit, integration, and load testing
  • Experience with Docker containers, Implementing Docker Containers, Container Clustering
  • Experience with container orchestration technology such as Kubernetes a big plus

Benefits

  • Bonus points if you have:
  • Design, research and develop state-of-the-art machine learning applications and algorithms to improve the lives of podcasters and podcast listeners around the world

Company info

  • As an integral part of the squad, you will collaborate with research scientists, data scientists and other engineers in prototyping and productizing brand-new ML at the intersection of speech processing and long-term user satisfaction.
  • We are flexible!

This listing is sourced directly from Zencastr's careers page and normalized into a canonical job model.