Machine Learning Engineer

Summary

Join Tether's dynamic Brain & AI team as a Machine Learning Engineer. You will develop and evaluate scalable deep learning algorithms for brain decoding initiatives, collaborating with data scientists on generative modeling and representation learning. The role involves identifying and resolving data processing bottlenecks, maintaining high code quality, and adapting algorithms for various computing environments. Tether offers a global, remote work environment and the opportunity to work on cutting-edge AI and neuroscience projects. This position requires strong Python programming skills, experience with deep learning techniques, and proficiency in managing unstructured datasets. A degree in a quantitative field and familiarity with specific deep learning libraries are preferred.

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

Benefits

• Remote work
• Global team