About the role
Title: Machine Learning Senior Platform & Infrastructure Engineer
Industry: Gaming
Location: Los Angeles, CA
Duration: 12 months
Responsibilities
- Build and operate Kubernetes, multi-node GPU clusters, networking infrastructure, and distributed ML training platforms.
- Design and scale game simulation infrastructure for parallel rollouts, data collection, training, and evaluation.
- Develop CI/CD pipelines, deployment automation, artifact management, infrastructure-as-code, and internal developer tools across cloud environments.
- Improve reliability, scalability, performance, cost efficiency, observability, reproducibility, auditability, and SLO-based operations.
- Support MLOps, security governance, incident response, root-cause remediation, and the mentoring and development of platform engineering talent.
Requirements
- Bachelor’s degree in Computer Science or a related field, or equivalent practical experience, with 3+ years of software engineering experience.
- Production experience operating distributed systems and reliable, high-scale infrastructure, including Kubernetes, AWS or GCP, infrastructure-as-code, and CI/CD.
- Experience with GPU infrastructure, including scheduling, multi-node orchestration, and resource optimization for long-running ML workloads.
- Strong Python skills and understanding of networking, microservices, infrastructure services, and distributed systems.
- Familiarity with MLOps practices such as model versioning, pipeline orchestration, experiment tracking, artifact management, and reproducible ML workflows; experience with distributed training, HPC, inference serving, high-performance networking, or game simulation is a plus.
Skills
- Kubernetes
- GPU infrastructure
- Distributed systems
- MLOps
- Python
- AWS
- GCP
- Infrastructure as code
- CI/CD
- Distributed ML training
Hourly rate is commensurate with experience and is an estimated range provided by WorkGenius.
ref_id: 9642c7ee-86bd-4c0a-84c0-30acb6c364df
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