Responsibilities
- Develop and evaluate scalable deep learning algorithms that are central to our brain decoding initiatives.
- Collaborate closely with data scientists to pioneer research in generative modeling and representation learning.
- Identify bottlenecks in data processing pipelines and devise effective solutions, improving performance and reliability.
- Maintain high standards of code quality, organization, and automatization across all projects.
- Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs.
Basic qualifications
- Strong programming skills in Python, with experience in developing machine learning algorithms or infrastructure using Python and PyTorch.
- Experience in deep learning techniques such as supervised, semi-supervised, self-supervised learning, and/or generative modeling.
- Proficient in managing unstructured datasets with strong analytic skills.
- Demonstrated project management and organizational skills.
- Proven ability to support and collaborate with cross-functional teams in a dynamic environment.
Preferred qualifications
- Degree in Computer Science, Statistics, Informatics, Information Systems, or another quantitative field.
- Familiarity with deep learning libraries such as Huggingface, Transformers, Accelerator and Diffuser.
- Hands-on experience in training and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs.
- Experience with data and model visualization tools.
Tags & focus areas
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