Nex
Software Engineer, ML Engineering
Vaga remota de Machine Learning Engineering com fit claro de localização do candidato.
Publicada1 de jul. de 2026
Países elegíveis2 países aceitos
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
ChinaHong Kong, RAE da China
Resumo da vaga
Software Engineer, ML Engineering
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
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 haves
- 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 haves
- 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
We Offer
- Competitive compensation package.
- Flexible working hours and vacation policy.
- Product-driven culture that treasures talents and individual growth.
- Front-row seat and hands-on experience with cutting edge technologies in the evolving gaming field
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