AI/ML Research Engineer
Tasks
- Build and maintain scalable data processing pipelines
- Build tools and utilities for rapid prototyping
- Collaborate to translate experimental ML approaches into production code
- Design and execute ML experiments with rigorous analysis
- Develop and deploy ML infrastructure for distributed training and inference
- Implement and optimize machine learning models for protein design
- Optimize model performance and computational efficiency
Perks/Benefits
- N/A
Skills/Tech-stack
AWS | Cloud Computing | Computational Biology | Data Processing | Data pipeline | Deep learning | Diffusion Models | Distributed Computing | Docker | ETL | GCP | GPU Optimization | Git | JAX | Kubernetes | LLM | MLOps | Machine Learning | Model Deployment | NumPy | Pandas | Protein Structure Analysis | Protein structure | PyTorch | Python | Scikit-learn | Software Engineering | Structure analysis | Testing | Version control
Education
Regions
Countries
States
Cities
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