Staff Machine Learning Engineer, ML Infrastructure - Offline
Tasks
- Design and operate large scale data pipelines for training datasets
- Develop distributed training infrastructure
- Enable large scale experimentation and model iteration
- Improve ML pipeline reproducibility and observability
- Integrate ML pipelines with workflow orchestration
- Lead architectural improvements for scalable reliable cost efficient offline ML platforms
- Optimize performance and resource utilization for distributed compute
Perks/Benefits
- Commute subsidy
- Competitive retirement pension plans
- Employee resource groups
- Employee stock ownership
- Generous vacation personal days
- Global employee assistance program
- Mental health and wellbeing programs
- Office Food Snacks
- Support for new parents through leave and family care programs
- Training and development programs
- Volunteering and donation matching program
Skills/Tech-stack
Apache Airflow | Apache Flink | Apache Spark | Automated testing | Data Lake | Data Pipelines | Data Validation | Data Warehouse | Distributed Computing | Flyte | Machine Learning | Machine Learning Workflows | Monitoring | PyTorch | Python | Ray | Ray Data | Ray Train | Streaming Platforms
Education
N/A
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