Develop computational models of neural circuits and brain function. Requires Python, scientific computing libraries, and research experience in computational neuroscience. PhD or equivalent required.
90k – 200k
HybridAI Research
About the role
Responsibilities
Read, analyze, and synthesize neuroscience, cognitive science, and computational neuroscience literature.
Develop biologically plausible computational models of neural circuits, brain regions, and large-scale brain systems.
Compare model predictions with experimental data and refine models accordingly.
Develop novel algorithms inspired by biological neural computation.
Analyze large-scale neural and behavioral datasets to inform and evaluate computational models.
Stay current with advances in neuroscience, machine learning, and computational modeling.
Propose and pursue original research directions that advance our understanding of brain computation.
Make novel scientific contributions to computational neuroscience through the development of new theories and models.
Document research findings and communicate results through technical reports, publications, and presentations.
Requirements
Experience programming in Python
Familiarity with scientific computing libraries such as JAX, PyTorch, NumPy, SciPy, or similar tools
Research experience in systems, computational, and theoretical neuroscience
Experience working with data analysis, statistics, or machine learning workflows
Ability to work independently and communicate technical findings clearly
Ph.D. or equivalent demonstrated expertise in Computational Neuroscience, Neuroscience, Computer Science, Physics, Electrical Engineering, Applied Mathematics, or a related discipline
Nice-to-Haves
Experience with machine learning or dynamical systems modeling
C++ programming experience
Familiarity with Linux, Git, and high-performance computing environments
Interest in neural circuit modeling, synaptic plasticity and learning, large-scale brain simulations, data-driven modeling of neural systems, or wet lab experiments
3-month full-time research fellowship at Base Labs focused on open-source LLMs and frontier AI. Fellows receive 1:1 senior mentorship, $15k stipend, full support, and a path to full-time roles while producing publishable research from the San Francisco office.
60k – 60k
HybridAI Research
Machine Learning Researcher, Multimodal LLMs
Bland AISan Francisco, CA
Develops next-generation multimodal LLMs integrating speech, text, tools, and real-time reasoning for conversational AI agents. Requires strong background in LLMs, multimodal models, fast experimentation, and production deployment experience.
140k – 250k
RemoteAI Research
Copy of Machine Learning Researcher, Audio
Bland AISan Francisco, CA
Conducts foundational research and develops scalable ML models for speech-to-text, text-to-speech, and neural audio codecs in real-time voice AI agents. Requires deep expertise in voice modeling, self-supervised learning, and production deployment at enterprise scale.
140k – 250k
RemoteAI Research
Forward Deployed Research Scientist
LabelboxSan Francisco, CA
Forward Deployed Research Scientist collaborates with frontier AI labs on data strategies, fine-tunes open-weight LLMs, runs ablation studies, and validates data impact for client projects. Requires MS/PhD in ML/NLP/CS, hands-on LLM fine-tuning, and fast-paced experimental rigor.
140k – 200k
HybridAI Research
Research Scientist - Simplex
AsteraEmeryville, CA
Develops theories of intelligence grounded in neural network internal structures, focusing on belief geometries in LLMs and biological brains. Conducts experiments bridging mathematics, ML interpretability, and safety research; requires PhD-level quantitative depth and hands-on coding.