Machine Learning Engineer II

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’s MusicIQ team builds and advances scalable, high-performance machine learning systems that support content intelligence and catalog serving. In this onsite role in Seattle, you will help design, evolve, and operate production ML infrastructure that powers music tagging, similarity, and customer experiences.

As a Machine Learning Engineer II, you will work across the full lifecycle of model and platform development, including building data pipelines, deploying models to production, and supporting offline and real-time processing paths.

Responsibilities

• Enhance core ML infrastructure for tagging music content and improve music similarity capabilities.
• Work with research scientists to deploy scalable ML models to production, improving model performance and architecture.
• Explore design options, prototype new technologies, and assess technical feasibility, including approaches such as AutoML and real-time ML serving systems.
• Collaborate with scientists to design and build data pipelines for processing massive datasets and scaling machine learning models.
• Develop and maintain platforms and services used to build, evaluate, and deploy machine learning models in real-world applications.

Requirements

• 3+ years of non-internship professional software development experience.
• 2+ years of non-internship experience designing or architecting systems, including design patterns and reliability and scaling for new and existing systems.
• 1+ years of software development engineer or related occupational experience.
• 1+ years designing and developing large-scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using C#, C++, Java, or Perl.
• 1+ years of Object Oriented Design experience.
• Bachelor’s degree (or foreign equivalent) in Computer Science, Engineering, Mathematics, or a related field.
• Experience programming with at least one software programming language.
• 3+ years of full software development life cycle experience, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Bachelor’s degree in computer science or equivalent.

Technologies

• C#
• C++
• Java
• Perl

Compensation and Location

• Location: Seattle, WA (onsite)
• Salary: USD 143,700 - 194,400 per year

Benefits

• Sign-on payments
• Restricted stock units (RSUs)
• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance) and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage
• 401(k) matching
• Paid time off
• Parental leave