The Role
We build end-to-end AI systems, core microservices, and infrastructures by leveraging cutting-edge technologies to impact millions with personalized user experiences everyday.
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.
You’ll join a team of hardworking engineers that are passionate about understanding what drives users’ long-term happiness with Zencastr, and how our recommendations and content affects that. 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.
What You'll Do..
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
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
Work with some of the brightest minds in signal processing
If This Describes You..
A postgraduate degree in Machine Learning, Mathematics, Computer Science, or a related quantitative field
5 + years experience in Python
3+ years experience in machine learning research, with a focus on speech
3+ years experience training or deploying neural networks
Significant experience with machine learning libraries like PyTorch, Tensorflow, Scikit-Learn
Experience with building and operating production-ready ML systems
Ability to lead design and implementation of major software components, systems, and features
You enjoy quickly building model prototypes
Experience with cloud technologies (Google Cloud, AWS, Modal)
You are a self-starter who drives your own projects and builds positive relationships with partners and colleagues to solve big multi-functional efforts from start to finish. You are able to succeed with minimal mentorship and process.
Bonus points if you 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 building APIs
Experience with Docker containers, Implementing Docker Containers, Container Clustering
Experience with container orchestration technology such as Kubernetes a big plus
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