ML Engineer II - Real-Time Music AI & Scalable ML Ops

DataJobs; Seattle (WA); On-site; USD 144,000 - 194,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance (medical, dental, etc

401(k) matching

Paid time off

Parental leave

Job summary

Amazon in Seattle is seeking a Machine Learning Engineer II to design, evolve, and operate production ML infrastructure powering music tagging, similarity, and customer experiences. This onsite role emphasizes end-to-end model and platform development, data pipelines, and deployment to production for real-time and offline paths.

You will collaborate with researchers and engineers on scalable models, data processing systems, and automated design options, including AutoML and real-time serving

Qualifications

• 3+ years of non-internship professional software development experience.
• 2+ years of design or architecting systems for scaling.
• 1+ years of software development engineer experience.
• 1+ years designing and developing multi-tiered distributed software applications.
• OO design experience required.

Responsibilities

• Enhance core ML infrastructure for tagging music content and improve similarity capabilities.
• Deploy scalable ML models to production with researchers.
• Design and prototype new technologies including AutoML and real-time ML serving systems.
• Build data pipelines for processing massive datasets and scaling models.
• Develop platforms and services to build, evaluate, and deploy ML models in real applications.

Skills

Software development

System design

OO design

Programming languages

SDLC

Education

Bachelor's degree in CS/Engineering/Math

CS-related degree or equivalent

Tools

C#

C++

Java

Perl

Job description

Amazon in Seattle is seeking a Machine Learning Engineer II to design, evolve, and operate production ML infrastructure powering music tagging, similarity, and customer experiences. This onsite role emphasizes end-to-end model and platform development, data pipelines, and deployment to production for real-time and offline paths.

You will collaborate with researchers and engineers on scalable models, data processing systems, and automated design options, including AutoML and real-time serving