🛠 Tech Stack

💼 About This Role

You'll join a globally distributed team working at the intersection of AI, neuroscience, and digital finance. Your core impact involves developing scalable machine learning models to decode neural activity for brain-computer interface technologies. This role offers strong exposure to research-oriented work while maintaining a practical focus on scalable engineering solutions.

🎯 What You'll Do

• Develop and train scalable deep learning models for brain decoding.
• Collaborate with research scientists on generative modeling and representation learning.
• Maintain ML pipelines ensuring high performance and reliability across distributed systems.
• Contribute to research experimentation, documentation, and scientific publications.

📋 Requirements

• Bachelor’s degree in a quantitative discipline (Computer Science, Math, Physics, etc.).
• 3+ years of experience in machine learning or deep learning.
• Strong Python skills and hands-on experience with PyTorch.
• Solid understanding of supervised, self-supervised, and generative deep learning techniques.

✨ Nice to Have

• Experience with Hugging Face, Transformers, Diffusers, or Accelerator.
• Experience with generative models, large language models, or neural data (EEG, fMRI, MEG).
• PhD-level research experience and publications in AI or neuroscience conferences.

🎁 Benefits & Perks

• 🌍 Fully remote work environment with global collaboration.
• 🧠 Work on cutting-edge AI and neuroscience technologies.
• 🔬 Exposure to advanced research in deep learning and brain-computer interfaces.
• 🚀 Fast-paced, innovation-focused culture with significant autonomy.
• 📈 Career growth in a rapidly evolving international organization.

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Take-Home Assignment· 3-4 hours