Research Scientist (Applied LLMs), London
Tasks
- Analyze and tune experimental results
- Collaborate with scientists and domain experts
- Contribute to machine learning research
- Create and lead machine learning research projects
- Create novel machine learning techniques
- Develop LLM driven approaches for drug discovery
- Implement and scale training and inference engineering frameworks
- Provide technical mentorship and guidance
- Report and present research findings
Perks/Benefits
Skills/Tech-stack
Agents | Alignment | Bioinformatics | Calculus | Computational Chemistry | Deep learning | Fine Tuning | Generative Models | Graph Neural Networks | Inference | JAX | Language Models | Large Language Models | Linear Algebra | Machine Learning | Model Architecture | Multi-parameter optimization | Neural Networks | NumPy | Pandas | Parameter optimization | PyTorch | Real-world datasets | Reasoning | Reinforcement Learning | SciPy | Statistics | TensorFlow | Test Time | Test-time Scaling | Tool use | Training
Education
Roles
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