AI/ML Specialist Solutions Architect

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for an AI/ML Specialist Solutions Architect based in Germany. Join a pioneering AI infrastructure environment where you will help organizations design and deploy scalable machine learning solutions. This role combines deep technical expertise with customer-facing collaboration, allowing you to influence how businesses leverage advanced AI platforms. You will act as a trusted advisor, guiding customers through complex AI workloads, distributed training environments, and production-scale deployments. Working closely with engineering and product teams, you will translate customer challenges into impactful solutions and product improvements. This opportunity is ideal for an experienced AI professional who enjoys solving complex problems, sharing knowledge, and shaping the future of AI adoption. Accountabilities Design customer-focused AI and machine learning solutions that maximize business value and align with technical and strategic objectives. Act as a trusted technical advisor for customers, helping them successfully adopt and scale AI infrastructure and services. Architect and support large-scale AI deployments, including distributed training environments involving multi-node and multi-GPU systems. Build strong customer relationships by understanding technical requirements, addressing challenges, and ensuring long-term satisfaction. Deliver technical content including presentations, documentation, whitepapers, manuals, and webinars for audiences with different levels of technical expertise. Collaborate closely with engineering and product teams to communicate customer feedback, influence priorities, and improve solutions. Support customers in moving AI workloads from experimentation and proof-of-concept stages into reliable production environments. Stay current with AI/ML technologies, frameworks, and infrastructure trends to provide high-quality technical guidance. Requirements 3+ years of experience working with cloud technologies in MLOps engineering, machine learning engineering, solutions architecture, or similar technical roles. Strong understanding of machine learning ecosystems, including models, AI use cases, workflows, and supporting tooling. Proven experience designing, deploying, and optimizing distributed training pipelin…