Senior Software Engineer
Job description
About the role
The role advances reverse-brain-engineering by building and operating infrastructure for large-scale model training and complex simulation. Decisions about architecture directly shape the robustness of systems that navigate research uncertainty. Custom reinforcement-learning environments translate neuroscience insights into simulation capabilities.
Software engineers turn product ideas into working code. Engineers work in small teams, review each other's work, and ship in small batches. Most teams follow agile practices such as sprints and daily standups. Engineers also write tests, fix bugs, and improve performance. The field values clear communication as much as technical skill. Engineers spend part of every week on planning, code review, and debugging, not just writing new code. The ability to explain a technical decision in plain words separates strong engineers from the rest.
Key facts
What you'll do
High-performance infrastructure is architographed to train large-scale models and run complex simulations, enabling ambitious reverse-brain-engineering work. Systems designed for research chaos support core reverse-brain-engineering objectives and maintain robustness under uncertainty. Custom reinforcement-learning environments are designed and optimized to align simulation capabilities with neuroscience insights, guiding experimental direction. Clean, fast, production-grade code is written to boost research velocity and convert prototypes into scalable systems that accelerate discovery. Technical bottlenecks, spanning low-level optimization to high-level system design, are tackled to ensure the research team remains unblocked and productive.
Requirements
A Bachelor's degree or equivalent experience is required for this position. Candidates must work in-person at the Emeryville HQ location. Visa sponsorship may be available for qualified candidates who meet criteria.
Practical notes
The role is full-time and operates in an in-person setting in Emeryville. Team collaboration is central, and the position may involve travel as project needs require. Typical interview steps
Hiring for engineering roles usually starts with a recruiter screen, followed by one or two technical rounds. Candidates often solve a coding problem, discuss past projects, and answer system design questions. Some loops include a take-home task. Final rounds typically cover team fit and give candidates a chance to ask questions. Interviewers look for how you break down an unfamiliar problem, not just whether you reach the answer. Practicing a few problems aloud and reviewing your own past projects are the best preparation.
Good to know
The role involves foundational infrastructure and simulation work in computational science. The position relies on distributed systems and low-level optimization skills to handle demanding workloads. The environment demands fast iteration, rigorous testing, and disciplined engineering practices. The work supports large-scale model training and neuroscience-inspired tools that drive innovation. The role operates within a foundation structure focused on long-term scientific advancement.
Questions to ask
Good questions to ask the employer in the interview: what does success look like in the first six months, how is the team structured, what is the current biggest challenge, and how are decisions made. Asking about growth paths and the review process is also well received. Employers expect questions, and good ones show preparation.
Career growth
Engineering careers usually progress from individual contributor to senior, staff, and principal levels. Some engineers move into management and lead teams of five to twenty people. Others stay on the technical track. Growth follows demonstrated impact, not tenure alone. A typical engineering ladder has clear levels with defined expectations for scope, quality, and mentorship. Moving up usually requires owning outcomes end to end rather than completing assigned tickets.
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.