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Job Description
We are looking for a technically-skilled deep learning engineer, oriented towards deep learning implementation. They will be responsible for:
- Implementing/Replicating Research Papers of interest. Mainly related to: Protein Design, Generative Models, Language Models.
- Perform literature review of relevant subjects when needed.
- Implementing/Testing deep learning research ideas based on literature review.
- Communicating their progress and views to their teammates efficiently.
- Staying up to date with state-of-the-art deep learning tools and papers on topics owned by the engineer.
Job Requirements
- Strong and proven knowledge of at least one of the well-known deep learning libraries (Keras+TensorFlow/Pytorch). Eg: Open Source Contributions, Github Projects, Kaggle Projects, Published paper implementations ... etc
- Either a formal education in Deep Learning-related Certificate OR A record of Online Deep Learning Courses + Books read on the topic.
- Strong communication skills to communicate with team members from DevOps, bioinformatics, and biology backgrounds.
- Familiarity with the following deep learning models/features: -- Basic Attention Paradigms -- Transformers -- CNNs -- LSTMs * Good Problem Solving skills.
- Ability to read and discuss research papers with other team members.
- Good culture-fits exhibit the values we believe in, more here: https://www.proteinea.com/careers-proteinea
Plus if:
- Experimented with Jax Python Library before for deep learning.
- Has any cloud experience, preferably AWS.
- Familiarity with state of the art research in the deep learning field.
