Staff ML Engineer

About the Company

This organisation is one of Germany's most ambitious AI scale-ups, backed by more than €20M in funding and already trusted by major enterprise clients with revenues exceeding €20B. The founders are serial entrepreneurs with multiple successful exits, and the current ML team includes talent from Amazon, Meta, Stability AI, Aleph Alpha and leading research institutes.

Their platform delivers enterprise-grade AI assistants capable of answering complex scientific, legal, and technical queries. With rapid customer growth and a significant increase in data volume on the horizon, they are now strengthening their senior technical leadership.

The Opportunity

This position sits at the heart of the company's next phase. As a Staff ML Engineer, you will operate with broad autonomy, defining where the biggest impact lies and shaping the evolution of a system built around ingestion, retrieval and agent capabilities.

Rather than following a predefined roadmap, you will identify the most valuable areas for improvement, introduce best practices, and guide the team through key architectural decisions as the platform scales from megabytes to terabytes of data.

This role blends deep engineering, applied research, and strategic influence, ideal for someone who wants ownership, freedom, and the opportunity to shape a frontier agentic AI system that will serve some of the world's most demanding enterprise use cases.

Key Responsibilities

• Identify and define the highest-impact improvements across ingestion, retrieval, and agent components to maximise accuracy and reliability.
• Diagnose suboptimal processes and lead architectural redesigns, introducing best-in-class frameworks and engineering patterns.
• Establish meaningful evaluation metrics, enhance existing assessment methods, and ensure metrics correlate directly with accuracy, cost and latency objectives.
• Drive the transition from external AI API usage to internally deployed, purpose-built models optimised for specific functions.
• Build scalable ML and data pipelines in preparation for a major shift from megabyte- to terabyte-scale datasets.
• Guide research and data-focused initiatives, improving retrieval strategies, model behaviour, and evaluation methodologies.
• Provide technical leadership across the team, mentoring senior engineers and enforcing strong engineering principles.
• Shape long-term technical direction, influencing both system design and ML research approaches.
• Operate with significant autonomy, determining priorities and leading initiatives that accelerate performance, efficiency, and scalability.

Essential Skills & Experience

• Proven experience designing and scaling LLM, RAG, or agentic systems in production settings.
• Strong expertise in model fine-tuning, PEFT, distillation, quantisation and high-performance inference.
• Deep understanding of retrieval pipelines, vector search and modern RAG architectures.
• Robust engineering capability using Python and PyTorch.
• Experience guiding technical direction or influencing architectural decisions in high-growth environments.
• Track record of elevating engineering teams through mentorship and best-practice leadership.

What Makes This Role Exciting

• Genuine ownership: You choose the direction of improvement rather than inheriting a rigid roadmap.
• Impact at scale: Your decisions directly influence how the system handles fast-growing enterprise demand and massive upcoming data expansion.
• Blend of engineering and research: Freedom to explore architectural redesigns while contributing to evaluation strategy, retrieval quality and model behaviour.
• High-calibre peers: Work with a team drawn from top global AI organisations.
• Foundational timing: Join at the moment when long-term architectural decisions are being made.

Benefits

• Meaningful equity participation.
• Fully remote within Germany.
• Clear progression towards Principal Engineer or early leadership roles.
• High-impact work within a well-funded, product-driven AI scale-up.