ML Researcher
San Francisco, CA$150k - $250k + equityFull-timePosted 3mo ago
About the role
AXION is building brain-computer interface technology to translate neural and sensor signals into user intent, with a focus on making interactions with digital devices accessible and seamless. The ML Researcher will define and build machine learning systems that translate neural and sensor signals into reliable, real-time user intent, bridging neuroscience, signal processing, and modern deep learning to run in production on constrained hardware.
Responsibilities
- Design and train state-of-the-art models for decoding intent from neural and physiological signals (e.g., EEG), including multimodal fusion with eye-tracking and contextual signals
- Build end-to-end ML pipelines: dataset design, labeling strategy, preprocessing, augmentation, training, evaluation, and deployment
- Develop algorithms for denoising, artifact rejection, and non-stationary signal modeling to improve robustness across users, sessions, and hardware conditions
- Explore and implement modern architectures (Transformers, state-space models, diffusion/denoising models, self-supervised learning) for time-series and multimodal learning
- Own offline + online evaluation frameworks, including real-time inference constraints (latency, stability, calibration, drift) and metrics aligned with user experience
- Partner closely with hardware and software engineering to integrate models into the product stack and iterate quickly from user feedback and field data
- Help in setting the technical direction for research at AXION: research roadmap, experiments, baselines, ablations, reproducibility standards, and publication strategy where appropriate
Qualifications
- 5+ years of professional experience in machine learning research and/or applied ML (industry or research labs)
- Strong Python skills and deep experience with modern ML tooling (e.g., PyTorch or JAX, experiment tracking, distributed training)
- Demonstrated ability to take ML projects end-to-end: idea → experiments → strong results → integration into real systems
- Excellent fundamentals in statistical learning, deep learning, and experimental rigor (ablations, leakage prevention, proper validation)
- Clear communication, strong engineering judgment, and a collaborative, low-ego approach in a fast-moving startup environment
Skills
Required:Machine learning researchPythonPyTorch or JAXEnd-to-end ML project executionStatistics and experimental rigorCommunication and collaboration
Nice to have:Time-series / multimodal learningReal-time ML deployment
Last updated Jul 26, 2026. Interested? Apply on the company site.
About AXION
Transforming neural activity into human ability.
AXION — Non-invasive Neural Interfaces
SCIENCELife Hands-freebci
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