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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, with a focus on customer engagement, technical architecture, and hands-on implementation.
Key Responsibilities
- Design and architect cloud infrastructure solutions for customers using technologies like Kubernetes, Kubeflow, OpenStack, and Spark
- Deploy, test, and hand over cloud solutions on-premise or in public cloud environments such as AWS, Azure, and Google Cloud
- Collect customer requirements and advise on open source applications and infrastructure
- Develop Kubernetes operators and Linux infrastructure-as-code using Python
- Deliver technical presentations and demonstrations of AI/ML capabilities to clients
- Collaborate with sales and product teams to influence roadmaps and achieve business targets
- Work directly with customers to solve complex data architecture and AI/ML deployment problems
- Participate in customer and industry events, including travel up to 30%
Requirements
- Exceptional academic track record from both high school and university, or a compelling narrative about your alternative chosen path
- Undergraduate degree in a technical subject or equivalent experience demonstrating technical proficiency
- 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 Platform
- 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
- 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
Personal learning and development budget of USD 2,000 per year
Annual holiday leave
Maternity and paternity leave
Recognition rewards
Team Member Assistance Program
Wellness Platform
Opportunity to travel to new locations to meet colleagues
Priority Pass and travel upgrades for long-haul company events
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