Machine Learning Scientist — Large Multimodal Models (Post-Training)
Tasks
- Build hyperparameter optimization workflows
- Collaborate with machine learning and software engineering teams to productionize systems
- Create benchmarking and evaluation frameworks
- Design reinforcement learning reward functions and training objectives
- Develop inference optimization techniques
- Implement reproducible experimentation and high quality ML code
- Research post training strategies for multimodal foundation models
Perks/Benefits
- Flexible holiday allowances
- Life assurance
- Pension contributions
- Private medical insurance
- Remote work option
Skills/Tech-stack
CUDA | Deep learning | Distributed Training | Docker | Efficient Fine Tuning | Fine Tuning | Hyperparameter Optimization | Inference Optimization | Kubernetes | Machine Learning | Mixed Precision | Optuna | PPO | Parameter efficient fine-tuning | PyTorch | Python | Quantization | RLAIF | RLHF | Ray Tune | Reinforcement Learning | Supervised Fine Tuning | Transformers | Weights and Biases
Education
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