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Are you excited to drive AI drug discovery forward by scaling SOTA models and optimizing neural nets on GPUs?
Qualifications
• Bachelor's/ Master's or PhD in Computer Science, Engineering, or a related field
• 5+ years of experience deploying AI/ML models in production settings
• Proficient in Python, C++, and deep learning frameworks like PyTorch or Jax
• Skilled in distributed training (e.g., DDP, FSDP) and model performance optimization
• Experience with GPU architectures, cloud platforms, and hardware tradeoffs
• Familiarity with low-level hardware tuning and custom CUDA kernel development
Key Responsibilities
• Develop cutting-edge AI models for drug discovery using deep learning frameworks
• Scale and optimize distributed training of large AI models on GPUs
• Enhance performance of AI models during both training and inference stages
• Communicate findings through documentation, presentations, and stay updated on AI advancements
• Contribute to impactful research at the AI-healthcare frontier
• Access to professional growth via conferences, workshops, and training
• 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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