About the company
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a MLOps Field Engineer based in Switzerland.
Responsibilities
- Design and architect AI/ML, MLOps, data engineering, and cloud infrastructure solutions aligned with customer workloads and business requirements.
- Work across the Linux technology stack, including networking, storage, containers, applications, and infrastructure.
- Architect and deploy solutions using Kubernetes, Kubeflow, OpenStack, Spark, and related open source technologies.
- Deliver solutions across on-premises environments and major public cloud platforms, including AWS, Azure, and Google Cloud.
- Engage directly with customers to understand technical and business requirements and recommend appropriate open source solutions.
- Deploy, test, troubleshoot, and validate technical solutions before handing them over to support or managed services teams.
- Develop infrastructure automation and Kubernetes capabilities using Python and other relevant technologies.
- Deliver technical presentations, demonstrations, workshops, and training sessions covering cloud, Linux, AI/ML, and open source technologies.
- Collaborate closely with enterprise sales teams to support customer engagements, develop opportunities, and achieve shared commercial objectives.
- Work with product and engineering teams to communicate customer requirements, provide technical feedback, and influence product and technology roadmaps.
- Travel internationally for customer engagements, industry events, internal events, and project-related activities, with travel potentially reaching 30% of working time.
Requirements
- Professional experience in MLOps, data engineering, big data, cloud infrastructure, or the deployment of machine learning and analytics solutions.
- Practical experience with Linux, virtualization, containers, networking, and cloud infrastructure.
- Experience with Kubernetes and familiarity with cloud platforms such as AWS, Azure, or Google Cloud.
- Working knowledge of MLOps, AI/ML infrastructure, data processing pipelines, distributed systems, or large-scale analytics environments.
- Intermediate Python programming skills, with experience in another language such as R or Rust considered an advantage.
- Understanding of open source technologies and an interest in enterprise applications of private cloud, machine learning, AI, data, and analytics.
- Ability to design technical architectures and translate complex customer requirements into practical infrastructure and solution designs.
- Strong customer-facing communication skills, with the ability to explain technical concepts through presentations, demonstrations, workshops, and discussions.
- Business-minded approach with the ability to balance technical quality, customer needs, and commercial objectives.
- Demonstrated problem-solving ability, initiative, and willingness to take ownership of complex projects.
- Strong written and spoken English with excellent presentation skills.
- A technical undergraduate degree or a compelling alternative educational or professional background.
- Willingness and ability to travel internationally for customer meetings, industry events, and company gatherings.
Conditions
- Geographically adjusted compensation based on location, experience, and performance.
- Performance-driven annual bonus or commission in addition to base compensation.
- Fully distributed work environment with twice-yearly in-person team sprints.
- Personal learning and development budget of USD 2,000 per year.
- Annual compensation review.
- Recognition rewards.
- 40 days of annual leave per year, including public holidays and company-wide holiday periods.
- Maternity and paternity leave.
- Team Member Assistance Program and Wellness Platform.
- Opportunities to travel internationally and collaborate with colleagues in different locations.
- Priority Pass access and travel upgrades for eligible long-haul company events.