The MLOps Field Engineer at Canonical is responsible for designing and deploying AI and machine learning infrastructure solutions for enterprise clients, working closely with customers to solve complex data architecture problems using open source technologies on cloud and on-premise environments.
Key Responsibilities
Design and deploy AI/ML infrastructure solutions for enterprise customers on cloud and on-premise environments
Work hands-on with technologies such as Kubernetes, Kubeflow, OpenStack, and Spark to implement cloud solutions
Collect customer requirements and advise on open source applications and cloud architectures
Deploy, test, and hand over solutions to support or managed services teams
Develop Kubernetes operators and Linux infrastructure-as-code using Python
Deliver presentations and demonstrations of AI/ML capabilities to clients
Collaborate with sales and product teams to influence roadmaps and achieve targets
Travel internationally up to 30% for customer meetings, events, and internal team sprints
Requirements
Exceptional academic track record from both high school and university, or a compelling narrative about an alternative chosen path
Undergraduate degree in a technical subject or equivalent experience demonstrating relevant skills
Experience in data engineering, MLOps, or big data solutions deployment
Experience with a relevant programming language, such as Python, R, or Rust
Practical knowledge of Linux, virtualization, containers, and networking
Knowledge of cloud computing concepts including Kubernetes, AWS, Azure, and Google Cloud
Intermediate level Python programming skills
Experience with Linux Debian or Ubuntu preferred
Ability to collect customer business requirements and advise on Ubuntu and relevant open source applications
Ability to deliver presentations and demonstrations of Ubuntu Pro and AI ML capabilities to prospective and current clients
Work across the entire Linux stack, from kernel, networking, storage, to applications, and architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack, and Spark
Experience deploying solutions on-premise or in public cloud environments
Ability to liaise with product teams to give feedback on requirements to influence roadmap
Ability to work collaboratively with sales teams to reach targets
Willingness to travel internationally up to 30% of the time for internal, external events, and customer meetings
Excellent written and spoken English with strong presentation skills
Strong interpersonal skills, curiosity, flexibility, and accountability
Self-motivated with a result-oriented approach and a drive to follow up and meet commitments
Ability to work in a multi-cultural, multi-national organization with appreciation of diversity
Thoughtfulness and self-motivation
Ability to jump into new projects and interact effectively with people
Willingness and ability to travel internationally for company events up to two weeks long
Benefits & Perks
Compensation/salary range is based on experience, performance, and location, with annual reviews and performance-driven bonuses or commissions
Distributed work environment with most colleagues working from home
Global travel up to 30% of time for internal, external events, and customer meetings
Annual holiday leave
Maternity and paternity leave
Team Member Assistance Program
Wellness Platform
Personal learning and development budget of USD 2,000 per year
Recognition rewards
Opportunity to travel to new locations to meet colleagues
Priority Pass and travel upgrades for long-haul company events
Ready to Apply?
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