Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)
Tasks
- Build data pipelines for training datasets
- Collaborate on experimentation and model iteration
- Contribute to offline ML platform architecture
- Monitor data quality and model reliability
- Optimize data processing and training performance
- Orchestrate multi stage ML pipelines
- Support distributed model training workflows
- Validate datasets for reproducibility
Perks/Benefits
- Commute subsidy
- Comprehensive health insurance
- Disability insurance
- Employee assistance program
- Employee resource groups
- Employee stock ownership
- Generous vacation
- Life insurance
- Mental health programs
- Office Food Snacks
- Parental leave
- Retirement pension plans
- Training and development programs
- Volunteering and donation matching
Skills/Tech-stack
Airflow | Apache Spark | Data Lakes | Data Pipelines | Data Validation | Data Warehousing | Distributed Systems | Flyte | Machine Learning | Model Training | Monitoring | PyTorch | Python | Ray | TensorFlow | Testing | Workflow Orchestration
Education
Regions
Countries
States
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