Lead Machine Learning Engineer (Foundation Models)
Tasks
- Architect pre training pipelines
- Build distributed training systems
- Design generative recommendation systems
- Integrate models into production environments
- Lead code and design reviews
- Mentor junior engineers
- Optimize transformer model architectures
Perks/Benefits
- Birthday leave
- Employee assistance programme
- FlexWork
- Flexible benefits
- Medical insurance
- Parental leave
- Term life insurance
- Volunteering leave
Skills/Tech-stack
C++ | DPO | Deep learning | DeepSpeed | Distributed Training | Efficient Fine Tuning | Expert parallelism | FSDP | Fine Tuning | Knowledge Distillation | LLMOps | Language Models | Large Language Models | LoRA | Long Context | Long context attention | MLOps | Machine Learning | Megatron-LM | Mixture of Experts | Multimodal Learning | Parameter efficient fine-tuning | Pipeline parallelism | Pretraining | PyTorch | PyTorch FSDP | Python | QLoRA | RLAIF | RLHF | Ray | Reinforcement Learning | Retrieval-Augmented Generation | Semantic Tokenization | Supervised Fine Tuning | Tensor Parallelism | Transformers
Education
N/A
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