Research Scientist: Energy Based Models
Job description
About the role
This role investigates foundational principles to advance AGI. The position connects biological intelligence, computational theory, and large-scale execution. The work targets understanding the brain's computational principles.
Research roles build new knowledge and test ideas. Researchers design studies, run experiments, and analyze results. The work spans academic labs, corporate R&D, and product research. Rigor, reproducibility, and clear reporting are the standards that matter. Research work is evaluated on rigor and reproducibility. Most researchers keep detailed lab books or version-controlled analysis code.
Key facts
What you'll do
Through this work, representations support distributed planning across multiple agents and scales.
Experiments evaluate causal representations and integration of sensory information within active inference frameworks.
Abstract mathematical frameworks are translated into scalable systems through collaboration with neuroscientists and software engineers. Cross-disciplinary teams convert theoretical constructs into implementations that operate at scale.
Open science practices reshape how research outputs are shared and evaluated in the community.
Requirements
A PhD in Computer Science, Electrical Engineering, Neuroscience, Physics, or a related quantitative field is required, with equivalent capability accepted for non-traditional backgrounds. Foundational knowledge in deep learning, graphical models, and information theory underpins advanced research expectations.
Expert-level coding skills in deep learning frameworks such as PyTorch and JAX are required, with an emphasis on clean and reproducible research code. Clean implementations ensure that research workflows remain robust and maintainable.
Demonstrated interest in core AI challenges including robustness, generalization, and common-sense reasoning is required. Curiosity about the computational principles of the mammalian brain drives persistent inquiry into architectures and learning.
The ability to thrive in a lean, fast-paced setting with high autonomy and direct influence on research direction is required. Startup-like conditions allow individuals to shape research direction with minimal organizational constraints.
Practical notes
The role is based in Emeryville HQ. The team operates as a small, lean group with high autonomy. Typical interview steps
Research interviews usually include a presentation of past work, a technical discussion, and sometimes a research proposal exercise. Candidates may be asked to design a study or critique a method. Depth of understanding is tested more than speed. Interviewers often ask you to present your past work in depth. Being ready to defend every methodological choice is the core preparation.
Good to know
Energy-based models and latent variable reasoning support modern unsupervised representation learning. Research workflows often combine mathematical theory with large-scale system implementation. Open science practices can accelerate scientific discovery and reproducibility. Foundational AGI research focuses on robustness, generalization, and common-sense reasoning. Collaborative team structures reduce organizational inertia and accelerate impact.
Questions to ask
Worth asking in any interview: how the team measures success, who the role works with daily, what the onboarding looks like, and what the company is trying to achieve this year. Asking what past hires did well is a strong final question. Keep the list short and pick the questions that matter most to you.
Career growth
Research careers grow from junior researcher to senior scientist, principal, and lab or research director roles. Some people move into applied research and product work. Publication record or demonstrable impact drives progression, depending on the setting. Research careers reward a strong publication or delivery record. Applied research roles value impact on products as much as novelty.
About the company
Astera is a private foundation on a mission to steer science and technology toward an abundant future for all. We believe the coming years will bring an era of unprecedented scientific and technological advancement as exponential progress in AI converges with central advances in other fields to dramatically accelerate innovation.