For this role you’ll bring a functional knowledge of build systems, code coverage, test automation, and security scanning to automate the deployment of our general-purpose robots’ control stack. The ideal candidate for this role will be a versatile, creative engineer with excellent communication skills and a firm grasp of modern practices in data and software engineering, operations, and security. The work you do will support the functionality and security of the world’s first human‑like intelligence in general purpose robots, enabling us to iterate on new innovations rapidly.Our Success CriteriaBring hands on experience with defining cloud infrastructure to support the development, packaging, and deployment of software to a hybrid environmentBolster your career experience by developing automated build, test, and deploy pipelines and supporting tools that enable rapid iteration/continuous improvementBuild reporting and monitoring solutions that provide continuous feedback to stakeholdersWrite custom tools and scripts to increase software and ML model development velocity and reliabilityExpand your security experience by incorporating security‑by‑design into new and existing software systemsQualificationsBachelor's degree in Engineering, Computer Science, or equivalent degree3+ years of hands‑on experience engineering production software in a cloud environmentExpertise in defining CI/CD pipelines and operating related infrastructureFamiliarity with machine learning training and runtime practicesWorking knowledge of security, identity and access management, and networking for machine public cloud providers (AWS/Azure/GCP)SkillsCI/CD pipeline design using Git Lab CI, Jenkins, or similarInfrastructure as code using Terraform, AWS CDK, Ansible, or similarFamiliarity with KubernetesFamiliarity with at least one programming language such as Python, Typescript, or C++Expert‑level knowledge of Unix, including shell scripting, file systems,



networking, and process managementExperience with security at the network, transport, and application layers (DNS-SEC, OWASP, HTTP, TLS, etc.)Experience with MLOps tools, such as Weights & Biases, Explicit ML, or MLFlow is desirableTraitsAbove all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problemsOptimistic listening and conflict resolution capabilitiesStrong communication and interpersonal skillsSelf‑motivated and able to solve problems independentlyObsession with bringing human‑like intelligence to machinesWorking at Sanctuary AISanctuary 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 Linked In as a Top Startup company.Compensation and BenefitsSanctuary 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 AIFounded in 2018 by Geordie Rose, Olivia Norton, and Ajay Agrawal, Sanctuary AI is a Vancouver, Canada‑based company. Sanctuary AI is on a mission to create the world’s first human‑like intelligence in general‑purpose robots that will help us work more safely, efficiently, and sustainably. And in the not‑too‑distant future, help us explore, settle, and prosper in outer space.#J-18808-Ljbffr

📌 Machine Learning Deployment Engineer (Vancouver)
🏢 Sanctuary AI
📍 Vancouver