Sr Machine Learning Engineer

Remote • $80k - $180k

Zencastr


Role Location

  • Remote

Compensation

$80k - $180k

Employees

11 - 25 people

Address

1575 E Ventnor Ave
Holladay, UT, 84121, US

Tech Stack

  • Node.js
  • TypeScript
  • JavaScript
  • Docker

Role Description

Empower the voices of the world @ Zencastr. If you want to push the world of podcasting into the future, come join a team who loves to live on the edge! We are a fully distributed team of smart people who are passionate about changing the world one voice at a time.

You should join us if :

  • You want to build machine learning applications that will improve the lives of podcasters around the world

  • You want to work with some of the brightest minds in signal processing

  • You have significant experience with a machine learning libraries like Tensorflow, Scikit-Learn, or PyTorch

  • You have a good understanding of DSP and ML fundamentals

  • You enjoy quickly building model prototypes

  • You have an eye for performance

  • You have good communication skills

What sets you apart:

  • You have a passion for high performance applications

  • You have significant open source contributions

  • You want to work in a fast growing startup. Which comes with the blood, sweat and tears of working to disrupt an established industry

  • You’ve tried to cure an itch either by creating or contributing to an open source project

  • You have empathy for the end user. A spec is a conversation starter, as an advocate for the end user you always are thinking about how to best serve their needs

  • You have an eye for code quality and you strive to uphold best practices in engineering, security, and design

Why you should choose us:

  • You’ll be working with world class engineers, Phd’s, machine learning engineers and designers in a fully distributed team

  • Work in an agile and fast changing environment

  • Equity commensurate to your contribution in a profitable company

  • Health insurance / vision / dental

  • Unique challenges and the support and talent to solve them

  • 4 weeks PTO

  • Freedom to work where you please

What we’re looking for: * Preferably: A postgraduate degree in Machine Learning, Mathematics, Computer Science, or a related quantitative field

  • 5 + years experience in Python, C++, or related language

  • Strong scripting skills in Python, Bash, or related scripting languages, as well as command line experience

  • Experience with various machine learning architectures and the parameters that affect their performance

  • Demonstrable knowledge of building and serving scalable machine learning solutions to a production environment

  • Ability to lead design and implementation of major software components, systems, and features

  • Experience with cloud technologies (Google Cloud, AWS)

Bonus points if you have:

  • Publications in peer-reviewed journals from a related field

  • Experience with recommendation systems

  • Experience with NLP frameworks

  • Experience with modern speech recognition 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

We are flexible! For the right candidate we ask: What do you need to do your best work?

About Zencastr

We are building the YouTube for podcasts

Company Culture

We found that we work well with people who love what they do and want to help creators. We are a bunch of music/audio nerds who believe we can change the world and fix some big problems in media. This app was launched from a jungle in Thailand so we could keep cost low and offer this service for free to users because we just wanted to help creators. This passion continues throughout the company today.

Interested in this role?
Skip straight to final-round interviews by applying through Triplebyte.