Cloud & MLOps Engineer

Nembrini Consulting is an international consulting and technology advisory firm based in Switzerland, supporting clients across Europe and globally. We specialize in business transformation, SAP and ERP consulting, finance and digital solutions, working with medium-sized companies and large international organizations, including large-scale international e-commerce projects. Our approach combines strong local presence, deep industry expertise and a pragmatic, results-oriented mindset. We act both as a strategic partner for clients and as a career platform for consultants, offering exposure to complex transformation programs, international projects and long-term professional development opportunities.

For one of our partners, we are looking for a Cloud & MLOps Engineer to design, build, and operate production‑grade ML and agentic pipelines for large‑scale AI systems. In this role, you will work at the intersection of cloud infrastructure, machine learning operations, and intelligent systems, enabling reliable, automated workflows for training, evaluation, deployment, and monitoring of AI agents in real‑world environments.

You will play a key role in taking AI systems from research to production, with high ownership, autonomy, and direct impact.

Start date:
January 2026

• EU or Swiss nationality or Swiss C permit
• 3+ years of hands‑on experience as an MLOps Engineer or Dev Ops/MLOps Engineer
• Strong cloud engineering experience on at least one major provider (AWS, Azure, or GCP)
• Bachelor + Master’s degree in Computer Engineering, Computer Science, or a closely related field
• Availability to work fully onsite in Switzerland (Lugano office and potentially client premises)
• Fluent English (written and spoken)

• Architect, build, and operate end‑to‑end ML and agentic pipelines
• Integrate model execution, data pipelines, evaluation loops, and orchestration into robust production systems
• Design and maintain scalable cloud infrastructure for ML workloads
• Develop and manage CI/CD and Continuous Training (CT) pipelines for ML systems
• Ensure system reliability, observability, security, and performance
• Collaborate closely with ML researchers, software engineers, and Dev Ops teams
• Automate infrastructure provisioning, configuration, and deployments
• Continuously improve time‑to‑production and operational stability of AI systems

• Bachelor + Master’s degree in Computer Engineering, Computer Science, or similar (strong academic background preferred)
• Strong Python skills for automation, orchestration, and tooling
• Solid experience with cloud platforms (AWS, Azure, GCP)
• Familiarity with cloud‑native ML services (e.g. AWS Sage Maker, Vertex AI, Azure ML)
• Proven experience deploying ML systems into production
• Hands‑on experience with containers and Kubernetes
• Strong knowledge of Infrastructure‑as‑Code and CI/CD pipelines
• Good understanding of networking, security, monitoring, and observability
• Ability to work independently while collaborating effectively with cross‑functional teams

• English: fluent (mandatory)
• Italian: fluent (not mandatory)
• German: nice to have (not mandatory)

• Experience in banking or regulated environments
• Exposure to agentic systems, distributed training, or large‑scale inference services
• Experience with monitoring, logging, and alerting stacks

• Switzerland‑based role
• Hybrid setup with approximately 50% remote work from Lugano and 50% on‑site at client location, depending on the project

• Permanent, full‑time position in Switzerland
• Competitive compensation aligned with seniority and market standards
• Access to cutting‑edge AI infrastructure and modern MLOps stacks
• High autonomy and strong ownership on production AI systems
• Direct impact on real‑world, large‑scale AI deployments
• Mentorship, continuous learning, and long‑term growth opportunities

• Mid‑Senior level

• Full‑time

• Engineering and Information Technology

• IT Services and IT Consulting

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