Nex
Software Engineer, ML Engineering
Rol remoto de Machine Learning Engineering con fit claro de ubicación del candidato.
Publicado1 jul 2026
Países elegibles2 países aceptados
Señal de senioritySenior
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
ChinaRAE de Hong Kong (China)
Resumen del rol
Software Engineer, ML Engineering
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
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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