Machine Learning Infrastructure Engineer, GenAI Technology
Tasks
- Collaborate to optimize compute utilization and training throughput
- Design and implement infrastructure for generative AI and machine learning workloads
- Design and operate distributed systems for model training and inference
- Develop and automate deployment and CI CD pipelines
- Document architecture and mentor engineers
- Drive security compliance and operational runbooks
- Evaluate and benchmark hardware and software technologies
- Implement observability monitoring and cost management
- Troubleshoot profile and optimize GPU and CPU performance
Perks/Benefits
- 401k match
- Employee wellness programs
- Family leave
- Health care benefits
- Parental leave
- Tuition assistance
- Volunteer opportunities
Skills/Tech-stack
Access Control | Amazon Web Services | Apache Airflow | C++ | CI/CD | CPU Performance Optimization | CPU performance | Cloud platform | Container Orchestration | Cost Optimization | Distributed Systems | GPU Computing | Go | Google Cloud | Google Cloud Platform | Incident Response | Infrastructure as Code | Kubeflow | Kubernetes | MLflow | Microsoft Azure | Monitoring | Observability | Performance optimization | Python | Ray | Reinforcement Learning | Rust | Secrets management | Security | Terraform | Web Services | “as-code”
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
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