Machine Learning Engineer — Training Optimization
Tasks
- Build training infrastructure for checkpointing and fault tolerance
- Develop architecture aware training strategies
- Implement advanced training techniques
- Improve distributed training strategies
- Monitor training performance metrics
- Optimize machine learning training pipelines
- Profile and resolve training performance bottlenecks
- Translate research concepts into production systems
- Tune training hyperparameters and numerical precision
Perks/Benefits
- Collaborative technical team
- Equity opportunities
- Fast feedback loops
- High ownership
- Opportunities for technical learning
Skills/Tech-stack
Backpropagation | Bfloat16 | Checkpointing | Data parallelism | Deep learning | DeepSpeed | Distributed Training | FSDP | Fault Tolerance | Float16 | Float8 | Gradient Checkpointing | Learning Rate | Learning Rate Scheduling | Machine Learning | Megatron | Model Parallelism | Numerical precision | Optimization Algorithms | Pipeline parallelism | Profiling | PyTorch | Zero
Education
N/A
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