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

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.

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

Software Engineer, ML Engineering

Key skills