Software Engineer, ML Infrastructure

Motional; Singapore; On-site; SGD 70,000 - 110,000; Full time

Job summary

Motional Singapore is seeking an engineer to design, build, and operate core ML infrastructure on Kubernetes. You will develop scalable services spanning data ingestion, processing, training, and evaluation for large-scale vehicle data workflows.

The role requires 2+ years in software engineering, a CS degree, and hands-on Kubernetes experience, with strong Python/Go skills and cloud platform familiarity. Ownership and quality are valued in this high-performance team.

Qualifications

• 2+ years of professional software engineering experience.
• BS or MS in Computer Science or a related technical field.
• Hands-on experience deploying applications on Kubernetes 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.
• Bonus: Ray Data/Train usage and GPU orchestration experience.

Responsibilities

• Design, build, and deploy core components of our ML infrastructure platform on Kubernetes.
• Develop robust and scalable services supporting the ML lifecycle from data ingestion to model evaluation.
• Write high-quality, maintainable code for high-throughput systems handling large data volumes.
• Own features and systems end-to-end from design through production deployment and operation.

Skills

Kubernetes

Python

Go

Distributed backend

Cloud platforms

Ownership

High-scale infra

Ray (bonus)

Education

BS in Computer Science

MS in Computer Science

Tools

Ray

Ray Data

Ray Train

Job description

Mission Sumary:

Our team builds the foundational infrastructure that empowers Machine Learning Engineers to develop the next generation of self-driving technology. We design and operate the high-performance, large-scale systems that process petabytes of vehicle data, run massive simulations, and train complex models. This is a software engineering role focused on building robust platforms, not an SRE position.

As an Engineer, you will be a key contributor to the team, owning the design and implementation of critical services that directly impact the pace of AV innovation.

What you'll do:

• 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.

What we're looking for:

• 2+ 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.

Bonus Points:

• Production experience with Ray, specifically leveraging Ray Data and Ray Train.
• Experience with GPU management or orchestration infrastructure, such as warm pools, smart scheduling, or specialized GPU frameworks.