Generative AI Engineer
Tasks
- Build dataset construction and quality assurance pipelines
- Build scalable distributed training pipelines
- Design and execute fine tuning experiments
- Design evaluation suites with automated benchmarks and human evaluation
- Document training methodology and results
- Implement parameter efficient fine tuning
- Implement safety and policy evaluations
- Manage model artifacts and ensure reproducibility
- Mentor engineers on fine tuning and evaluation
- Operate GPU training jobs and recover training state
- Optimize training throughput with mixed precision and efficient attention
- Translate LLM research into production ready recipes
- Tune hyperparameters and optimizer configurations
Perks/Benefits
- N/A
Skills/Tech-stack
Adapter-Tuning | Benchmarking | DPO | Direct Preference Optimization | Distributed Training | Efficient Attention | Efficient Fine Tuning | Evaluation | FSDP | Fine Tuning | GPU Cluster | Human Feedback | Human evaluation | Hyperparameter Tuning | Learning from Human Feedback | LoRA | Mixed Precision | Parameter efficient fine-tuning | Pipeline parallelism | Policy Evaluation | Preference optimization | PyTorch | Python | QLoRA | RLHF | Reinforcement Learning | Reinforcement Learning from Human Feedback | Safety evaluation | Sequence Packing | Supervised Learning | Transformer | Zero
Education
Roles
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