Senior ML Infrastructure Engineer — Kubernetes Platform

MOTIONAL SINGAPORE PTE. LIMITED

Singapore

On-site

SGD 120,000 - 180,000

Full time

11 days ago

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Job summary

Motional Singapore Pte. Limited is seeking a Senior Software Engineer to design and build scalable ML infrastructure platforms on Kubernetes.

You will own components from design through production, tackling high-throughput data pipelines and petabyte-scale workloads. You will collaborate with ML engineers to enable faster experiments, write clean, robust code in Python or Go, and deploy on AWS, GCP, or Azure.

Qualifications

  • 4+ years of professional software engineering experience.
  • BS or MS in Computer Science or a related technical field.
  • Hands-on experience developing and deploying applications on Kubernetes (k8s) is a must.
  • Experience building or working on high-scale infrastructure or distributed backend systems.
  • Strong proficiency in Python, Go, or a similar language.
  • Solid experience with a major cloud provider (AWS, GCP, Azure).
  • A strong sense of ownership and a passion for building high-quality software.

Responsibilities

  • Design, build, and deploy core components of our ML infrastructure platform on Kubernetes.
  • Develop robust and scalable services that support the entire ML lifecycle, from data ingestion and processing to model training and evaluation.
  • Write high-quality, maintainable code for high-throughput systems that handle petabytes of data.
  • Own features and systems end-to-end, driving them from initial design through to production deployment and operation.

Skills

4+ years of software engineering
Ownership mindset
High-quality software

Education

BS/MS in Computer Science or related

Tools

Kubernetes
Python
Go
AWS
GCP
Azure

Job description

Motional Singapore Pte. Limited is seeking a Senior Software Engineer to design and build scalable ML infrastructure platforms on Kubernetes.

You will own components from design through production, tackling high-throughput data pipelines and petabyte-scale workloads. You will collaborate with ML engineers to enable faster experiments, write clean, robust code in Python or Go, and deploy on AWS, GCP, or Azure.

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