Senior Machine Learning Engineer (Remote)

Zencastr; New York (NY); Hybrid; USD 120,000 - 160,000; Full time

Job summary

A leading technology company is seeking a machine learning engineer to enhance the podcast creation experience. This role involves designing cutting-edge ML applications and collaborating with cross-functional teams. Ideal candidates have a postgraduate degree in a related field, experience with Python, and a strong background in machine learning and speech processing. Join a passionate team dedicated to optimizing user satisfaction through innovative technology.

Qualifications

• 5+ years experience in Python.
• 3+ years experience in machine learning research with focus on speech.
• Experience with building and operating production-ready ML systems.

Responsibilities

• Design, research, and develop state-of-the-art machine learning applications and algorithms.
• Collaborate with engineering partners and colleagues in large multi-functional efforts.
• Drive forward audio and text capabilities within the ML team.

Skills

Python

Machine Learning

Neural Networks

Speech Processing

Cloud Technologies

DevOps

Education

Postgraduate degree in Machine Learning or related field

Tools

PyTorch

Tensorflow

Scikit-Learn

MongoDB

SQL

Docker

Kubernetes

Job description

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

How to apply

Apply at https://jobs.ashbyhq.com/zencastr/c6a9c3b0-f260-4820-bb97-e78142eabd1e

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