Machine Learning Engineer (100% remote India)

At Tether, we are at the forefront of integrating artificial intelligence with brain-computer interface technologies

Our projects leverage deep learning, generative models, and representation learning to decode and interpret brain activity

With our foundation in both established and cutting-edge AI infrastructure, our mission is to bridge the gap between AI and neuroimaging, driving innovation that’s not only revolutionary but also accessible, transparent, and privacy-focused

Job Description:

We are looking for a motivated and skilled machine learning engineer to join our dynamic Brain & AI team

This role focuses on developing AI models that enhance our understanding of neural mechanisms and apply this knowledge to real-world applications

You will be instrumental in pushing the boundaries of what’s possible in AI and neuroscience, helping to solve some of the most complex and fascinating challenges in the field today

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