Machine Learning Engineer — Training Optimization
Tasks
- Build and maintain training infrastructure
- Collaborate with research teams on training strategies
- Define and monitor training performance metrics
- Evaluate and integrate advanced training techniques
- Improve distributed training approaches
- Optimize large scale model training pipelines
- Profile and resolve performance bottlenecks
- Translate research concepts into production systems
- Tune training components
Perks/Benefits
- Continuous learning
- Equity opportunities
- Experimentation friendly environment
- Technical quality focus
Skills/Tech-stack
AMD GPU | BF16 | Backpropagation | Checkpointing | Data parallelism | DeepSpeed | Distributed Training | FP16 | FP8 | FSDP | Fault Tolerance | GPU Training | Gradient Checkpointing | Learning Rate | Learning Rate Scheduling | Megatron | Model Parallelism | Multi-GPU | Multi-GPU Training | Multi-node | Multi-node Training | NVIDIA GPU | Numerical precision | Optimization Algorithms | Pipeline parallelism | Profiling | PyTorch | Zero
Education
N/A
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