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Job Description
The MLOps Field Engineer role involves designing and deploying AI and machine learning infrastructure solutions for enterprise customers using open source technologies, cloud platforms, and Kubernetes, while providing technical guidance, demonstrations, and customer support in a remote, global environment.
Key Responsibilities
- Design and deploy AI/ML infrastructure solutions on private and public cloud platforms.
- Work hands-on with cloud technologies, deploying, testing, and handing over solutions to support teams.
- Develop Kubernetes operators and Linux infrastructure-as-code using Python.
- Architect cloud infrastructure solutions such as Kubernetes, Kubeflow, OpenStack, and Spark.
- Collect customer requirements and advise on open source applications and cloud solutions.
- Deliver presentations and demonstrations of AI/ML capabilities to clients.
- Collaborate with product teams to provide feedback and influence development roadmaps.
- Work with sales teams to achieve business targets and support customer engagements.
- Travel internationally up to 30% for events, customer meetings, and internal team activities.
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 them on Ubuntu and relevant open source applications
- Professional written and spoken English with excellent presentation skills
- Ability to travel internationally for company events up to two weeks long, and customer or industry meetings
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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