Sanctuary's technical organization is built around four department Heads, each owning a vertical domain: ML, Software, Robot Software, and Hardware. This role sits as a peer to the four department Heads, reports directly to the CTO, and is accountable for ensuring the full system, across all four verticals, is scalable, interoperable and architected with a 2-3 year view toward product deployment at commercial scale.
You will make architectural bets with multi-year consequences, initiate cross-cutting technical work, and be expected to disagree with existing technical directions when evidence warrants it. The right candidate will have the depth to win technical arguments on merit, the conviction to hold positions under pressure, and the judgment to know which hills are worth contesting.
ResponsibilitiesCross-System Architecture
Own the architecture of the interfaces between ML and Simulation, Software, Robot Software, and Hardware. Your decisions define how the system composes for the next 2 to 3 years.
Identify where the current architecture has structural limits (rising coordination costs, late-surfacing integration issues, hidden coupling between verticals) and build the case, with evidence, for what needs to change.
Drive architectural reviews that span vertical boundaries. Your presence in a cross-team design discussion should change its outcome.
Technical Strategy and Roadmap
Hold and defend the 2 to 3 year technical vision for the full platform. Form independent positions on where robot learning and simulation, deployment infrastructure, and systems architecture are headed, and work with Product to translate conviction into the roadmap.
Provide the technical lens on product go-to-market: identify where technical capability should shape what Sanctuary takes to market, and where product requirements should drive architectural change.
Present a defensible multi-year systems strategy to the CTO and leadership. You are expected to make long-horizon bets and be accountable for them.
Recommend paradigm shifts when evidence supports them. Kill architectural directions that are not working.
Scalability and Deployment Architecture
Own the scalability and reproducibility of the full build-test-release pipeline across verticals. The release path needs to be simple, visible, and repeatable.
Design the deployment architecture that makes Sanctuary's intelligence hardware-agnostic, deployable across in-house and third-party commercial and industrial robotic hardware.
Set architectural standards for training infrastructure at a systems level: sample efficiency, computational cost, and scalability across the full platform, not just individual experiments.
Driving system reliability across the full platform, ensuring that as we scale deployments, the systems our customers and operators depend on are robust, observable, and recoverable.
Execution
Build and improve cross-cutting infrastructure end-to-end, from simulation environment interfaces through to real-hardware deployment pipelines.
Maintain deep technical fluency across the full stack: ML training systems, sim-to-real transfer, runtime software, and deployment infrastructure. You do not need to be the deepest expert in each, but you need enough depth to make sound architectural calls at every interface.
A track record of architectural decisions that shaped system-level architecture in real-world robotics or complex systems, not just individual experiments. You have made calls that constrained what others built.
Experience taking systems from R&D into production on real physical hardware, in robotics, AV, embedded, or industrial. You have shipped to the real world, not just to simulation.
AI/ML fluency to make sound architectural calls at the ML-to-runtime boundary. You do not need to be the deepest ML expert, but you do need the depth to make the call.
Experience making multi-year architectural bets and defending them under pressure, including killing directions that are not working.
Experience operating as a technical authority in a cross-functional environment: defining new architectural standards or functions, leading cross-team reviews, and influencing engineers who do not report to you.
Publications are welcome but not required.
Hands-on experience deploying learned models on physical robots or hardware.
A Ph.D. or advanced degree in a relevant field, or an equivalent body of shipped work.
Published or open-source work with real community adoption, as one signal of technical influence.
Production Python development (3.8+) with a high bar for code quality in training and inference systems.
Working knowledge of ML frameworks (e.g. PyTorch) sufficient to reason about training and inference systems.
Familiarity with simulation environments and sim-to-real workflows is a plus (Isaac Gym, MuJoCo, or equivalent).
Working knowledge of ROS2 and real-time robotics software constraints.
Familiarity with deployment infrastructure: CI/CD pipelines, release artifact management, and build systems at scale.
Familiarity with Jira, Confluence, or equivalent engineering tooling.
*This role involves travel to the United States and, occasionally, other international destinations. Candidates must be able to meet the applicable travel and entry requirements for the role.
Working at Sanctuary AI
Sanctuary AI is an equal opportunity employer; employment with Sanctuary AI is governed based on skills, competence, and qualifications and will not be influenced in any way by race, color, religion, gender, national origin/ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, mental or physical disability, or any other legally protected status. In 2023, Sanctuary AI moved into a state-of-the-art office facility and has been recognized by LinkedIn as a Top Startup company.
Compensation and Benefits
Sanctuary offers a market-leading compensation package that includes competitive salaries, equity stakes, and a full suite of benefits for permanent employees, encompassing health coverage, paid time off, cutting-edge work facilities, and worksite flexibility by role. Our commitment to fairness ensures that our total compensation consistently surpasses market standards.
About Sanctuary AI
Founded in 2018, Sanctuary builds humanoid robots and a novel control system for them that integrates symbolic logic and reasoning with data-driven robot foundation models. We use our robots to collect vision, audio, touch, and proprioception data from the perspective of the robot while they perform real-world work tasks. We use that data to train multimodal robot foundation models. Because our systems are vertically integrated, we can design, deploy, and refine at scale. Our mission is to create the world's first human-like intelligence platform for robots.
Sanctuary AI Vancouver, British Columbia, CAN Office
Vancouver, British Colombia, Canada
