ML Systems Eng: Training Pipelines & Prod Infra Remote

Nex; Singapore; Remote; SGD 155,239 - 245,795; Full time

Benefits offered by this job

Competitive compensation

Flexible working hours

Cutting-edge tech exposure

Job summary

Nex is hiring a Software Engineer in the ML Engineering track to build the foundations powering our platform’s ML capabilities. You will shape training pipelines, data workflows, and model integration systems to accelerate experimentation and production readiness.

You’ll tackle data infrastructure, real-time inference, and research tooling in a tight-knit team, with ownership of core technology areas and a strong emphasis on reliability and scalability.

Qualifications

• 3+ years of professional software engineering experience building production ML systems or training infrastructure.
• Proficiency in Python and at least one other systems language.
• Hands-on experience with PyTorch or TensorFlow in production or research environments.
• Experience building ML training pipelines or data workflows.
• Familiarity with model deployment, inference optimization, or MLOps practices.

Responsibilities

• Design and build training pipelines, data workflows, and model integration systems.
• Develop infrastructure that accelerates research iteration and reduces turnaround time.
• Build systems for data collection, curation, and preprocessing at scale.
• Create tools and automation that move experiments toward production readiness.
• Optimize data pipelines for reliability, performance, and observability.
• Collaborate with ML researchers to understand needs and remove blockers.
• Work on model serving infrastructure and integration with the production framework.
• Write clean, well-tested code and participate in code reviews.
• Contribute to shared tools, infrastructure, and cross-role projects.
• Work with Engineering Manager and Tech Lead to align priorities and direction.

Skills

Python

PyTorch

TensorFlow

ML pipelines

MLOps

Tools

Docker

Job description

Nex is hiring a Software Engineer in the ML Engineering track to build the foundations powering our platform’s ML capabilities. You will shape training pipelines, data workflows, and model integration systems to accelerate experimentation and production readiness.

You’ll tackle data infrastructure, real-time inference, and research tooling in a tight-knit team, with ownership of core technology areas and a strong emphasis on reliability and scalability.