Silicon Valley Robotics Center is built by a small, cross-disciplinary team of robotics engineers, researchers, operators, and educators. We structure this page around the roles you will encounter when you work with us rather than around individual profiles.
Profile photos and full individual bios are coming soon. In the meantime, if you need to speak with someone in a specific role, contact us at contact@roboticscenter.ai and we will schedule a direct introduction.
Our operations are split across four functional groups: research, hardware, data, and customer. Each group has an experienced lead who is accountable for the customer-facing work in their area. Within each group, individual engineers rotate across customer engagements so that knowledge does not silo into one person. We deliberately keep the team small enough that every engineer understands the state of every active project.
We hire for range. Most of our engineers have shipped research code, operated robots physically, written customer-facing documentation, and debugged production systems in the field. That versatility is what lets us take on hardware, data, and fleet work simultaneously instead of specializing narrowly.
Our research director owns the technical roadmap across imitation learning, reinforcement learning, and vision-language-action (VLA) models. They set data quality standards, approve evaluation protocols, and coordinate with academic partners on joint publications. If your engagement touches model training or benchmark evaluation, the research director will be involved in scoping. They also author our state-of-robotics research digest alongside the research team.
Our lead data engineer oversees episode collection, annotation, and delivery pipelines. They maintain the internal data platform, the tooling that operators use on the collection floor, and the export scripts that package episodes in LeRobot, RLDS, and HuggingFace-compatible formats. If you have a custom data collection engagement, you will review schemas, sensor modalities, and quality reports with this person directly.
Our education lead runs the academy, guides, glossary, tutorials, and workshops. They coordinate the editorial calendar with the research team to make sure new tutorials align with what is actually working in robotics research today. They also handle school and university outreach, including class visits, curriculum support, and student competitions hosted at the Mountain View campus.
Our teleoperation manager leads the operators who remotely pilot robots for partners. They maintain training curricula for new operators, run quality control across sessions, and design the safety and intervention workflows that keep robots and people safe in production environments. For customers running deployed fleets, they also coordinate shift schedules and incident reporting.
Our hardware lead manages vendor relationships, inbound inspection, outbound shipping, and the showroom demo pipeline. If you are buying or renting a robot through our store, this person has handled it in person. They also coordinate repair and refurbishment with our technicians and maintain the condition-grading process that determines rental pricing.
Our research engineers implement and benchmark imitation learning policies, VLA model fine-tuning pipelines, and RL environment integrations. They are the ones who actually train, evaluate, and compare models on customer data. They also contribute to open-source projects where it helps the community, and they publish internal benchmark results for the team to reference.
Our customer success engineers are the first technical point of contact for anyone using our products and services. They handle onboarding, integration support, incident triage, and follow-up. They work closely with the research and hardware teams to make sure that the answers customers receive reflect what the underlying systems actually do, not what a sales deck claims they do.
Our operations lead runs the showroom, the training bay, scheduling, and facility safety at both the Mountain View and Allston locations. They coordinate with shipping providers on inbound and outbound freight, schedule visits from partners and press, and handle everything from badge access to catering when the space hosts events. They are usually the first person you will see when you walk in.
We hire deliberately. Most of our team came in through a multi-week paid project rather than a traditional interview loop, which lets both sides evaluate fit on real work. Every engineer on the team has shipped something publicly visible, whether an open-source library, a published paper, a production robot deployment, or a comparable artifact that lets us evaluate their craft. We do not use leetcode-style interviews.
We are a small team and keep hiring measured. Role openings are posted on our join page when we have capacity for new colleagues. If you are interested in the company but no role is posted that fits, you are welcome to introduce yourself at contact@roboticscenter.ai.
We work hard and in-person most of the week at the Mountain View and Allston campuses because robotics engineering is fundamentally hands-on. You cannot debug a gripper over video call. That said, we respect personal time, we compensate fairly, and we do not glorify overwork. Our engineers are expected to keep up on the field (papers, releases, open-source) on the clock, not on nights and weekends.
We write a lot internally. Every engineering decision that will outlive a single meeting is documented, linked, and made searchable. We expect customer-facing writing to meet the same standard; if a tutorial is wrong, we want to know about it and fix it the same day.
If you would like to speak directly with someone in a specific role about your project, email us and request a call. We will pair you with the right engineer, not a generalist intermediary. For prospective hires, we are also happy to host informal conversations over coffee at the Mountain View showroom.
Contact us to schedule a direct introduction →
A typical weekday at the Mountain View campus starts with a short operational standup that covers inbound shipments, outbound deliveries, showroom visitors, and safety notes. From there, the teams split: data operators head to their collection cells, teleoperators log in to scheduled sessions, research engineers work on ongoing policy training or analysis jobs, and the hardware team processes inspections, staging, and crating. The showroom is open for walk-ins and scheduled demos throughout the day. Customer success engineers field support tickets, customer calls, and onboarding work alongside their research or hardware responsibilities.
Afternoons often include a cross-team working session on a specific customer project or a paper-reading segment where someone walks the team through a recent paper that might affect how we do things. We end the day with a written summary from each team so that context carries across time zones and days off. Nothing is required to be done at home; the team is encouraged to fully disconnect after hours unless they are on a customer incident rotation.
When a new customer engagement begins, it is assigned an accountable owner from one of the four functional groups depending on the nature of the work. The owner runs the scoping conversation, authors the proposal, and remains the primary point of contact through delivery. For cross-functional engagements, a shared internal document tracks decisions, milestones, and open questions so that any team member can pick up where another left off without losing context.
We review every active engagement in a weekly internal standup. That rhythm keeps delivery timelines honest, surfaces risks early, and lets the research, data, and hardware teams share lessons learned from customer-facing work. Customers do not sit in those meetings, but they receive a concise weekly status update covering progress, blockers, and upcoming milestones. Nothing on an engagement is allowed to go dark for more than five working days without a written reason.
Regardless of title, every engineer at SVRC is expected to be fluent with a baseline set of knowledge and tools that keeps the company coherent. That baseline includes Python for data pipelines and analysis, ROS or ROS 2 for robot communication, modern imitation learning training stacks (LeRobot, HuggingFace, PyTorch), and enough hardware literacy to safely power up, move, and shut down the robots we sell. Every engineer spends time on the collection floor during their first 90 days so they understand what data actually looks like before they start optimizing pipelines for it.
Beyond full-time staff, we work with a small group of part-time advisors and contributors who specialize in specific areas (legal, finance, export controls, mechanical design review). These advisors contribute on a project basis and are not listed individually on public channels unless they have given us written permission. If a particular engagement benefits from one of their advisory hours, we disclose the connection and any potential conflict of interest up front.
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