At a Glance
- Tasks: Automate deployment of cutting-edge robots' control systems and enhance their functionality.
- Company: Join Sanctuary AI, a top startup creating human-like intelligence in robots.
- Benefits: Competitive salary, equity, health coverage, flexible work options, and paid time off.
- Other info: Dynamic workplace with opportunities for growth and innovation.
- Why this job: Be part of revolutionary tech that shapes the future of robotics and AI.
- Qualifications: 3+ years in cloud software engineering and CI/CD pipeline expertise required.
The predicted salary is between 135000 - 165000 $ per year.
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 new 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
Machine Learning Deployment Engineer in Vancouver employer: Sanctuary AI
Sanctuary AI is an exceptional employer that fosters a culture of innovation and collaboration in the heart of Vancouver, Canada. As a Machine Learning Deployment Specialist, you will not only contribute to groundbreaking advancements in robotic intelligence but also enjoy a supportive work environment that prioritizes employee growth through continuous learning opportunities and cutting-edge projects. With a focus on work-life balance and a commitment to security and efficiency, Sanctuary AI offers a unique chance to be part of a transformative journey in technology.
