AI/ML Specialist Solutions Architect

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.

• 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 pipelines across multi-node and multi-GPU environments.
• Hands-on experience with machine learning frameworks such as PyTorch, JAX, TensorFlow, Hugging Face, or similar technologies.
• Strong knowledge of cloud infrastructure, DevOps practices, and modern AI deployment approaches.
• Experience with programming languages such as Python, Go, Java, or C++.
• Familiarity with technologies including Kubernetes, Slurm, Docker, Helm, Git, Terraform, and infrastructure-as-code practices.
• Excellent written and verbal communication skills, with the ability to explain complex technical concepts to both technical and non-technical audiences.
• Experience deploying production inference infrastructure or scaling ML pipelines from prototypes to production is considered a strong advantage.

Benefits

• Competitive compensation package.
• Opportunity to work on impactful AI infrastructure projects shaping the future of machine learning.
• Flexible work options, including remote opportunities across Europe.
• High level of ownership and autonomy in a fast-growing technology environment.
• Career development opportunities with continuous learning and exposure to advanced AI technologies.
• Collaboration with talented international teams of engineers and AI specialists.
• Innovative culture focused on experimentation, growth, and meaningful impact.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.

We appreciate your interest and wish you the best!

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