Software Engineer
Job description
About the role
Hardware and software development for non-invasive brain interfaces defines this role. Teams create products that serve millions and advance understanding of the brain.
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
Software replaces manual scripting to streamline workflows for engineers and neuroscientists. Systems transform radio and audio campaigns plus research objectives into structured data for analysis.
Databases and services manage project lifecycles, coordinating design, implementation, testing, and deployment activities.
Interfaces present complex information clearly to help teams evaluate and interact with solutions.
Collaboration on radio and audio campaigns clarifies requirements and resolves challenges to accelerate delivery of robust software.
Requirements
Strong engineering and physics first principles guide architectural decisions and trade-offs.
Full-stack web development experience using Python and Typescript builds consistent and maintainable products.
Infrastructure engineering practices with Kubernetes, AWS, and Terraform ensure reliable and scalable deployments.
A computer science or similar engineering degree provides foundational knowledge for complex problem-solving.
A history of shipping high-impact projects demonstrates execution and adaptation based on customer feedback.
High integrity supports professional judgement and rigorous decision-making across the software lifecycle.
Practical notes
The role is based in San Francisco. US work authorization is required. 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
Work in this field centers on hardware and software that interface with the brain to improve outcomes. Teams rely on cutting-edge tools for hardware, software, and research capabilities. Projects aim to create products that serve millions of people now and billions in the future. Rapid iteration helps teams learn quickly about the brain and refine their solutions. Collaboration across disciplines drives progress in non-invasive ultrasound stimulation and imaging.
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
At Nudge, our mission is to develop the best technology for interfacing with the brain to improve people's lives. We're starting with an approach that we believe can help the most people the fastest, and also allow us to learn as much about the brain as possible: developing a non-invasive, ultrasound-based device that can stimulate and image the brain at high resolution and depth.