Senior ML & Distributed Systems Engineer | Scale & Impact

Amazon Web Services (AWS); Mountain View (CA); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Sign-on payments

RSUs

Health insurance

Medical insurance

Dental insurance

Vision insurance

Prescription insurance

Basic Life & AD&D insurance

Supplemental life plans

EAP

Mental Health Support

Medical Advice Line

Flexible Spending Accounts

Adoption and Surrogacy Reimbursement

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Web Services (AWS) is seeking an architect to design and build a large-scale machine learning platform for Amazon Personalize. You will lead the end-to-end development of scalable, fault-tolerant storage and query systems and mentor cross-disciplinary teams.

This role requires 5+ years of software development experience with leadership in system design and architecture; a BS in CS or equivalent is preferred. Join us to shape next-generation personalized recommendations.

Qualifications

• Requires 5+ years of professional software development experience.
• Leadership in system design and architecture.
• Bachelor's degree in computer science or equivalent preferred.

Responsibilities

• Architect and develop a large-scale ML platform.
• Design scalable, fault-tolerant distributed storage and query systems.
• Collaborate with cross-disciplinary teams.

Skills

Distributed Systems

Machine Learning

System Architecture

ML Pipelines

Software Development

Scalability

Fault-tolerant Systems

Design Patterns

Education

Bachelor's degree in Computer Science

Job description

Amazon Web Services (AWS) is seeking an architect to design and build a large-scale machine learning platform for Amazon Personalize. You will lead the end-to-end development of scalable, fault-tolerant storage and query systems and mentor cross-disciplinary teams.

This role requires 5+ years of software development experience with leadership in system design and architecture; a BS in CS or equivalent is preferred. Join us to shape next-generation personalized recommendations.