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 Criteria

Bring hands on experience with defining cloud infrastructure to support the development, packaging, and deployment of software to a hybrid environment

Bolster your career experience by developing automated build, test, and deploy pipelines and supporting tools that enable rapid iteration/continuous improvement

Build reporting and monitoring solutions that provide continuous feedback to stakeholders

Write custom tools and scripts to increase software and ML model development velocity and reliability

Expand your security experience by incorporating security‑by‑design into recent and existing software systems

Qualifications

Bachelor's degree in Engineering, Computer Science, or equivalent degree

3+ years of hands‑on experience engineering production software in a cloud environment

Expertise in defining CI/CD pipelines and operating related infrastructure

Familiarity with machine learning training and runtime practices

Working knowledge of security, identity and access management, and networking for machine public cloud providers (AWS/Azure/GCP)

Skills

CI/CD pipeline design using GitLab CI, Jenkins, or similar

Infrastructure as code using Terraform, AWS CDK, Ansible, or similar

Familiarity with Kubernetes

Familiarity 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 management

Experience with security at the network, transport, and application layers (DNS-SEC, OWASP, HTTP, TLS, etc.)

Experience with MLOps tools, such as Weights & Biases, ClearML, or MLFlow is desirable

Traits

Above all else, a consistently positive attitude and a willingness to do whatever it takes to create robust solutions to complex problems

Optimistic listening and conflict resolution capabilities

Strong communication and interpersonal skills

Self‑motivated and able to solve problems independently

Obsession with bringing human‑like intelligence to machines

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 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.

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📌 Machine Learning Deployment Engineer (British Columbia)
🏢 Sanctuary AI
📍 British Columbia