Machine Learning Engineer (100% remote- Dubai)

Machine Learning Engineer (100% remote- Dubai)

Join Tether and Shape the Future of Digital Finance

At Tether, we're not just building products, we're pioneering a global financial revolution. Our cutting-edge solutions empower businesses from exchanges and wallets to payment processors and ATMs to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

About The Job

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. 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.

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 automation across all projects.
• Adapt machine learning and neural network algorithms to optimize performance in various computing environments, including distributed clusters and GPUs.

• 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.

• 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.