Software Engineer, ML Engineering

Location: Hong Kong or Remote

Type: Full Time

The Role

As a Software Engineer at Nex, you will contribute to building the technical foundations that power our platform's most demanding capabilities. In the ML Engineering track, you will build the infrastructure that accelerates machine learning research: training pipelines, data workflows, model integration systems, and the tools that enable rapid experimentation. Your work ensures researchers can iterate reliably and move experiments toward production readiness.

The role offers the opportunity to work on deeply technical problems in machine learning systems, data infrastructure, sensing technologies, and real-time inference. You will be part of a small, highly technical team that values both specialization and collaboration, with clear ownership of core technology areas.

The Mindset

You are drawn to solving complex technical challenges at the intersection of research and production engineering. You care deeply about building systems that are reliable, performant, and maintainable. You thrive in environments where technical depth matters, where your expertise in ML systems, distributed computing, or real-time software directly shapes what the platform can do.

What You’ll Do

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 their needs and remove technical blockers

Work on model serving infrastructure and integration with the production framework

Write clean, well-tested code that maintains high engineering standards

Participate in code reviews and help raise the engineering bar across the team

Contribute to shared tools, infrastructure, and cross-role projects (20% Time)

Work with the dual-leadership model (Engineering Manager and Tech Lead) to understand priorities and technical direction

Document systems and decisions to support team knowledge sharing

Must Have

3+ years of professional software engineering experience in building production ML systems, training infrastructure, or research platforms

Proficiency in Python, additional experience with at least one other systems language (C++, C#, Java, Rust, or Go)

Hands-on experience with PyTorch or TensorFlow in production or research environments

Experience building or maintaining ML training pipelines or data workflows

Familiarity with model deployment, inference optimization, or MLOps practices

Nice To Have

Experience with distributed training systems or GPU-accelerated computing

Knowledge of data versioning, experiment tracking, or ML metadata management

Familiarity with containerization (Docker) and orchestration tools

Contributions to open-source ML projects or research publications

Experience working in small, high-performance technical teams

Background in startups, high-growth environments, or consumer product companies

Passion for pushing technical boundaries and deep problem-solving