Machine Learning Scientist — Large Multimodal Models (Post-Training)
Tasks
- Build hyperparameter optimization and experimentation workflows
- Collaborate to productionize models evaluation and inference services
- Create and maintain benchmarking and evaluation frameworks
- Design reward functions and training objectives for reinforcement learning
- Develop inference optimization techniques for high throughput evaluation
- Research and develop post training strategies for multimodal foundation models
- Write and maintain research and engineering code
Perks/Benefits
- 401k matching
- Company paid healthcare
- Dining
- Flexible spending accounts
- Onsite gym
- Remote work
- Uncapped vacation
- Voluntary life insurance
Skills/Tech-stack
CUDA | Distributed Training | Docker | Efficient Fine Tuning | Fine Tuning | Kubernetes | LoRA | Mixed Precision | Optuna | PPO | Parameter efficient fine-tuning | PyTorch | Python | Quantization | RLAIF | RLHF | Ray Tune | Reinforcement Learning | Supervised Fine Tuning | Transformer | Weights and Biases
Education
Regions
Countries
States
Cities
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