Senior ML Engineer, Voice Assistant — NLU in Production

Roku; Austin (TX); Hybrid; USD 150,000 - 190,000; Full time

Benefits offered by this job

Hybrid work model

Remote Fridays

Job summary

Roku’s Entertainment Assistant team seeks experienced machine learning engineers to advance the core of Roku's Entertainment Assistant. You will work on state-of-the-art algorithms and cloud solutions, taking concepts from proof of concept to production.

Ideal candidates have 5+ years in ML/AI for NLU/ASR or advanced degrees with 3+ years, plus hands-on experience with large-scale systems, big data tools, and transformer-based models in production. Hybrid work model with in-office collaboration.

Qualifications

• Apply ML/AI to NLU or related domain with production experience.
• Build and deploy large-scale production systems and cloud components.
• Strong CS fundamentals and ability to write algorithms with ease.
• Experience with transformer-based models in production is a plus.
• Experience with big data tools and languages such as Java, Python, or C++.

Responsibilities

• Design and develop software and algorithms for Roku’s state-of-the-art entertainment assistant.
• Design and develop software components for high-availability and high-performance cloud solutions.
• End-to-end responsibility from proof of concept to production.
• Hands-on experience building large-scale production systems.
• Collaborate across teams to leverage best talent and ideas.
• Own initiatives and make pragmatic technical decisions.

Skills

ML/AI for NLU

Production systems

Algorithms

CS fundamentals

Self-driven

Education

Bachelor’s Degree preferred

Tools

Spark

EMR

S3

Airflow

Java

Python

C++

Job description

Roku’s Entertainment Assistant team seeks experienced machine learning engineers to advance the core of Roku's Entertainment Assistant. You will work on state-of-the-art algorithms and cloud solutions, taking concepts from proof of concept to production.

Ideal candidates have 5+ years in ML/AI for NLU/ASR or advanced degrees with 3+ years, plus hands-on experience with large-scale systems, big data tools, and transformer-based models in production. Hybrid work model with in-office collaboration.