AI Product Manager

AI Product Manager - Relocation to Denmark

Department: Product

Employment Type: Full Time

Location: Germany

Reporting To: Head of Product

At Factbird, we’re redefining how manufacturing runs. By combining hardware, firmware, cloud, and AI, we turn raw production data into real, measurable impact on factory floors around the world.

We’re building fast, scaling with purpose, and solving problems that matter. Now, we’re looking for an AI Product Manager with a strong machine learning and data foundation—someone who doesn’t just talk about AI, but understands how it’s built and shipped in real-world environments.

This is a high-impact, hands‑on product role at the core of Factbird’s growth.

As our AI Product Manager, you’ll define the AI product vision, own the roadmap, and drive execution from idea to launch — and beyond. But this isn’t a “surface-level” AI role. You’ll work closely with AI engineers and data teams as a true technical partner — shaping features based on a deep understanding of machine learning models, data pipelines, and production constraints.

Reporting to the Head of Product, you’ll play a key role in shaping how our AI platform scales — and how our customers create measurable value on the factory floor.

This role is based in Copenhagen, Denmark, where you’ll work closely with our product and engineering teams.

If you’re currently based elsewhere, don’t worry — we offer relocation support for the right candidate and will help make your move as smooth as possible.

• Define AI product direction: Own and drive the AI product vision — focused on solving real production bottlenecks through robust, scalable ML solutions.
• Turn ML capabilities into real features: Translate machine learning opportunities into concrete product features. Work closely with AI engineers to scope models, define inputs/outputs, understand constraints, and ensure production readiness.
• Design with data in mind: Partner with data engineers to define data requirements, ensure data quality, and build strong pipelines that support reliable model training, validation, and monitoring.
• Drive technical decision-making: Understand model limitations, trade‑offs, drift, latency, edge vs. cloud processing, and performance constraints in industrial environments — and use that insight to guide prioritization.
• Own performance and outcomes: Define and track both model performance metrics (precision, recall, drift, stability) and business KPIs (uptime, cost savings, throughput improvements).
• Launch, learn, iterate: Drive structured experimentation, MVP validation, and iterative improvements based on real‑world production data.
• End‑to‑end ownership: Manage AI‑driven products throughout their full lifecycle — tightly integrated with hardware, firmware, and cloud infrastructure.

You’re a builder with a technical backbone. You thrive in scale‑up environments where ownership is high, pace is fast, and impact is visible. You’re comfortable discussing model architecture, data pipelines, and deployment strategies — and you can bridge the gap between engineering depth and business value.

You care about AI — but even more about what it enables in the real world. You want to ship systems that factories depend on, not just experiment in isolation.

• Strong foundation in Machine Learning / Data Engineering: You have hands‑on experience with ML systems, data engineering, or similar technical roles. You understand how models are trained, validated, deployed, and monitored in production environments.
• Experience bringing ML into production: You’ve worked on AI/ML features that moved beyond prototypes and into real customer‑facing products.
• Comfortable with data tools: Experience working with SQL, Python, and understanding data pipelines, feature engineering, drift detection, and performance monitoring.
• Manufacturing or industrial experience: You understand production realities and can translate factory‑floor challenges into scalable digital products.
• Product management experience (3+ years): Ideally within SaaS, industrial tech, AI‑driven products, or production‑focused platforms.
• Experiment‑first mindset: You validate ideas…