Machine Learning Engineer- GPU

Bioptimus is seeking a Machine Learning Engineer- GPU to improve medical research using state-of-the-art machine learning algorithms. You'll work with interdisciplinary teams to build foundation models of biology for AI applications in biomedical innovation.

Key Responsibilities:

• Implement and apply advanced machine learning methods, particularly in foundation models, representation learning, large language models, and generative AI.
• Contribute to methodological research to unlock novel applications.
• Craft high-performance CUDA kernels and manage GPU clusters.
• Extract maximum performance from modern GPUs for efficient model inference and training.
• Integrate low-level efficient code in high-level MLOps frameworks.

Requirements:

• MSc or PhD in Computer Science or related field, or equivalent experience.
• Expert in GPU programming and distributed computing.
• Strong experience with deep learning frameworks (TensorFlow, PyTorch, Jax).
• Practical expertise in representation learning, large language models, and generative AI.
• Excellent Python coding skills and best practices.
• Strong analytical and communication skills.

This role offers the opportunity to work at the intersection of healthcare/biology and AI, contributing to groundbreaking research in biomedical innovation. Join a dynamic team setting the foundations for the development and application of foundation models in biomedical research.

Location: London, Paris, Nantes, or Remote