Senior Software Engineer, Platform & Infrastructur

Responsibilities

• Build and operate Kubernetes, multi-node GPU clusters, and networking infrastructure for distributed ML bot training and policy evaluation.
• Design infrastructure for large-scale simulation environments, parallel rollouts, data collection, training, and evaluation.
• Build CI/CD, deployment automation, artifact management, and infrastructure-as-code across cloud environments.
• Improve platform reliability, cost efficiency, performance, reproducibility, auditability, and operational maturity.
• Build observability, monitoring, alerting, health indicators, and SLO-aligned dashboards for infrastructure and ML workloads.
• Develop internal APIs, control planes, templates, and developer tooling for distributed training and evaluation workflows.
• Support MLOps workflows including automated training pipelines, model artifact management, experiment tracking, and reproducible ML lifecycle operations.
• Build security and governance controls, manage production incidents, drive root-cause remediation, mentor engineers, and support recruiting for platform roles.

Requirements

• Bachelor’s degree in Computer Science or a related field, or equivalent practical experience.
• At least 3 years of software engineering experience with meaningful infrastructure, platform engineering, or SRE experience.
• Experience operating distributed systems in production under real load.
• Strong experience with Kubernetes, AWS or GCP, infrastructure-as-code, CI/CD, deployment automation, and production tooling.
• Experience with GPU compute infrastructure, including scheduling, multi-node orchestration, and resource optimization for long-running training workloads.
• Proficiency in Python and understanding of networking, microservices, core infrastructure services, and distributed systems fundamentals.
• Familiarity with MLOps workflows including model versioning, pipeline orchestration, experiment tracking, artifact management, and reproducible ML workflows.
• Experience with distributed training or HPC frameworks, inference serving, systems languages, high-performance networking, Unreal/client-server architecture, and AI-assisted development tools is desired.
• Passion for games and player experience is desired.

Benefits

• Open paid time off policy.
• Flexible work schedules.
• Medical, dental, and life insurance.
• Parental leave for the employee, spouse/domestic partner, and children.
• 401k with company match.