Remote Machine Learning Engineer

Summary

Join Tether's dynamic Brain & AI team as a Machine Learning Engineer. This role centers on developing AI models to enhance our understanding of neural mechanisms and apply this knowledge to real-world applications. You will collaborate with data scientists, develop scalable deep learning algorithms, and optimize performance in various computing environments. The position requires strong Python programming skills, experience with deep learning techniques, and proficiency in managing unstructured datasets. You will be instrumental in pushing the boundaries of AI and neuroscience, tackling complex challenges in the field.

Requirements

• 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

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

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