Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad PhD)
Tasks
- Build and maintain training data pipelines
- Collaborate on experimentation and model iteration
- Ensure dataset validation monitoring and testing
- Evolve offline machine learning platform architecture
- Improve reproducibility and reliability
- Optimize performance and efficiency of data processing and training systems
- Orchestrate multi stage machine learning pipelines
- Support distributed model training workflows
Perks/Benefits
- Commute subsidy
- Comprehensive health insurance
- Disability insurance
- Employee assistance program
- Employee resource groups
- Employee stock ownership
- Generous vacation and personal days
- Life insurance
- Mental health & wellbeing programs
- Office snacks
- Parental leave
- Retirement pension plans
- Training and development programs
- Volunteering and donation matching program
Skills/Tech-stack
Apache Airflow | Data Pipelines | Data Processing | Data Validation | Distributed Systems | Flyte | Large Scale Data | Large-scale | Large-scale Data Processing | Machine Learning | Model Training | Monitoring | PyTorch | Python | Ray | Spark | TensorFlow | Testing
Education
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