Alljoined

Machine Learning Researcher

San Francisco

Sponsorship not specified$140k-$250kDetected 260 days ago

PythonCode ReviewTemporalMachine LearningDeep LearningPyTorchNLPResearchCommunicationCollaboration

About the role

We're seeking a talented Machine Learning Researcher to join our core R&D team.
You will work closely with leading experts in neural decoding and AI, pushing the boundaries of what's possible in brain computer interfaces.

Collaborate with a team of neuroscientists and ML engineers to create scalable, end-to-end neural decoding solutions.
Our goal is to develop a general consumer interface to completely transform what we can do at home and work.
Options for housing support

Technical Expertise:
A track record of high-quality research demonstrated by publications in top ML conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).
Strong proficiency in Python and PyTorch, familiarity with ML tooling, and distributed training.
Experience working in a production-quality codebase with modern code review standards.
Educational Background & Experience:
Multimodal Representation Learning (CLIP-style contrastive objectives, masked autoencoding)
Generative Modeling (diffusion, transformer-decoders, latent-GANs)
Temporal Sequence Modeling (state-space models, STFT-aware transformers, RWKV)
$140,000 - $250,000/year + equity
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range.

Bachelor's degree in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Mathematics, Biomedical Engineering, etc), with 5-7 years of experience in ML research or applied ML engineering
Graduate degree (M.S., Ph.D.) in Computer Science or a related domain (e.g., AI, Computational Neuroscience, Biomedical Engineering) with 3+ years of experience in ML research or applied ML engineering.
Candidates with a Ph.D. and/or experience in high profile ML research labs are strongly preferred.

$140,000 - $250,000/year + equity
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range.

Health insurance
Develop, train, and refine state-of-the-art deep learning models for neural decoding, building on the latest advancements in ML architectures (e.g., transformers, diffusion models, etc).
We apply deep learning research to large scale EEG datasets collected on affordable hardware to decode images, text, and video initially, and eventually moving to internal thought.

We are state-of-the art in capabilities and are fully vertically integrated.
We are actively growing our world-class team of researchers to build the next interface to improve individual lives as well as the well-being of society as a whole.

This listing is sourced directly from Alljoined's careers page and normalized into a canonical job model.