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Are you excited to drive AI drug discovery forward by scaling SOTA models and optimizing neural nets on GPUs?
Qualifications
1. Bachelors, Masters, or PhD in Computer Science, Engineering, or a related field
2. 5+ years of experience deploying AI/ML models in production settings
3. Proficient in Python, C++, and deep learning frameworks like PyTorch or Jax
4. Skilled in distributed training (e.g., DDP, FSDP) and model performance optimization
5. Experience with GPU architectures, cloud platforms, and hardware tradeoffs
6. Familiarity with low-level hardware tuning and custom CUDA kernel development
Key Responsibilities
1. Develop cutting-edge AI models for drug discovery using deep learning frameworks
2. Scale and optimize distributed training of large AI models on GPUs
3. Enhance performance of AI models during both training and inference stages
4. Communicate findings through documentation, presentations, and stay updated on AI advancements
5. Contribute to impactful research at the AI-healthcare frontier
6. Access to professional growth via conferences, workshops, and training
7. Work within an inclusive, collaborative culture focused on innovation and continuous learning
If you meet 60-70% of the requirements, I would love to hear from you. Click the Easy Apply button!
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