Machine Learning Researcher
US$140,000 – US$250,000 / yr base salary
Posted 5 Nov 2025
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 3–7 yrs
- Management level
- Individual contributor
- Employment
- On-Site
- Contract
- Full-time
- Visa sponsorship
- Offered
| Base salary | US$140,000 – US$250,000 / yr |
|---|
Field of studyArtificial Intelligence, Biomedical Engineering, Computational Neuroscience, Computer Science, Mathematics (or related)
Study levelBachelor's or higher
About Alljoined
Alljoined is creating a future where humans are fully understood and augmented by technology. Our work solves the communication bottleneck between humans and computers by decoding thoughts from the brain, entirely non-invasively. We apply deep learning research to large scale neural datasets to decode internal thought directly. By advancing the frontier of neural decoding, we aim to unlock meaningful breakthroughs in human wellness and capability.
About the Role
We are looking for a talented Machine Learning Researcher to join our core R&D team. You will design and implement advanced machine learning models for EEG-based neural decoding, contribute to high-impact research, and help build the foundational infrastructure behind our brain-decoding systems.
We are looking for someone who can work independently and evaluate hypotheses without external intervention. You will be working closely with experts in neuroscience and are expected to bring ML expertise to the problems they are trying to solve. This role sits at the intersection of ambitious research and rigorous engineering: you will explore novel modeling approaches while translating promising ideas into reliable, production-quality systems.
What You’ll Work On
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Develop, train, and refine state-of-the-art deep learning models for neural decoding, drawing on recent advances in architectures such as transformers and diffusion models.
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Explore novel methods for modeling high-frequency, time-series EEG data alongside several adjacent data modalities.
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Translate research insights into production-grade code that integrates seamlessly with our in-house BCI stack.
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Collaborate with neuroscientists and machine learning engineers to build scalable, end-to-end neural-decoding systems.
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Publish findings at leading machine learning and AI conferences, including NeurIPS, ICML, ICLR, and CVPR.
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Contribute to open-source communities where appropriate.
You May Be a Good Fit If You Have
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A bachelor’s or master's degree in computer science or a related field—such as artificial intelligence, computational neuroscience, mathematics, or biomedical engineering—and five to seven years of experience in industrial machine learning research; or
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A PhD in computer science or a related field—such as artificial intelligence, computational neuroscience, or biomedical engineering—and at least three years of experience in machine learning research or applied machine learning engineering.