Senior AI Scientist
Tasks
- Apply and validate scaling laws
- Apply gradient checkpointing
- Apply mixed precision training
- Debug optimizer instability and gradient pathologies
- Define technical direction for next generation models
- Design and apply RLHF objectives
- Design and experiment with loss functions
- Design and train large scale transformer models
- Design next token prediction objectives
- Design optimizers and learning rate schedulers
- Diagnose and resolve training instabilities at scale
- Execute distributed foundation model training
- Experiment with contrastive objectives
- Implement tensor parallelism and pipeline parallelism
- Navigate compute vs data tradeoffs
- Own model architecture choices for text and multimodal
- Use FSDP and ZeRO 3 for large scale training
Perks/Benefits
- Annual bonus opportunity
- Company RRSP contribution
- Equity awards
- Hybrid work
- Insurance coverage
- Paid Holidays
- Paid time off
- Remote work
Skills/Tech-stack
ALiBi | Adafactor | AdamW | Attention | BF16 | Chinchilla Scaling | Contrastive Learning | DPO | Deep learning | FP8 | FSDP | Function design | GRPO | Gradient Checkpointing | Grouped Query Attention | Learning Rate | Learning Rate Scheduling | Lion | Loss Function | Loss function design | Mixed Precision | Mixture of Experts | Mixture of Experts Routing | Next Token Prediction | Pipeline parallelism | RLHF | ROPE | Representation Learning | Scaling Laws | Tensor Parallelism | Transformer | Warmup Scheduler | ZeRO 3
Education
Roles
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