(Senior) Applied ML Engineer IPAI (m/f/d)

• Several years of experience as an Applied ML Engineer, Machine Learning Engineer, ML Platform Engineer, or in a comparable senior, hands-on role.
• Strong grounding in machine learning fundamentals, including model training, evaluation, and optimization.
• Experience with working close to users or customers, translating real-world needs into technical solutions, is highly valued.
• Practical experience with technologies and tooling across the ML flywheel (data management, model training and evaluation, model deployment and operation, agentic workflows). Python skills and familiarity with the Python ML/AI ecosystem are a plus.

Introduction text

Would you like to play an active and hands-on role in shaping the development of IPAI?

As an innovation platform for applied AI, we pursue the goal of successfully bringing artificial intelligence into use in companies and institutions. With IPAI, we have set ourselves the ambition of becoming the "Global Home of Human AI". We are creating a space for successful AI transformation and collaboration, generating further momentum for a true AI hotspot in Europe.

You are a senior, hands-on Applied Machine Learning Engineer with a strong focus on technical leadership and real-world impact. You are responsible for ensuring that ambitious ideas across the IPAI ecosystem turn into robust, end-to-end ML systems that actually work in practice. Operating close to members and partners, you bring the engineering depth, architectural judgment, and delivery capability required to make IPAI an effective platform for applied AI.The role combines forward-deployed engineering with platform thinking: hands-on where necessary, strategic where required, always focused on enabling others to succeed.

Your tasks

• Make IPAI members successful. You work directly with partners to design, prototype, and implement ML solutions that address concrete, high-impact problems.
• Cater to the entire ML product cycle. You help build end-to-end ML systems, spanning data and metadata management, model training and evaluation, deployment, and monitoring.
• Provide technical leadership and architectural guidance. You help teams navigate tool choices, system design, and trade-offs across modern ML stacks.
• Operate as a forward-deployed engineer. Where required, you embed with members and partner to unblock project progress, reduce technical risk, and accelerate delivery.
• Collaborate closely across IPAI, aligning engineering work with product strategy, partner management, and ecosystem needs.
• Strengthen IPAI’s technical foundation. You are contributing to reusable patterns and platform components, mentor others and share best practices.