AI Engineering Manager
Springer Nature opens the doors to discovery for researchers, educators, clinicians and other professionals. Every day, around the globe, our imprints, books, journals, platforms and technology solutions reach millions of people. For over 180 years our brands and imprints have been a trusted source of knowledge to these communities and today, more than ever, we see it as our responsibility to ensure that fundamental knowledge can be found, verified, understood and used by our communities – enabling them to improve outcomes, make progress, and benefit the generations that follow.Â
Job Title: AI Engineering Manager
Department: Springer Nature AI Labs
Location: Groningen
Company: Springer Nature
Who we are
At Springer Nature AI Labs (SNAIL), we’re shaping the future of scientific publishing through responsible, human-centred AI. Our team is at the forefront of integrating advanced AI technologies to optimize processes and enhance the user experience for researchers and academics worldwide. We value a collaborative work environment where ideas flourish, and innovation is encouraged. With our curiosity-driven, impact-first culture, we focus on delivering AI innovation at scale
always with integrity and in close collaboration across functions. Our commitment to long-term growth ensures that our people are nurtured and developed to reach their full potential.
Who you are
You are a driven and collaborative leader with a solid foundation in AI and Machine Learning. You have a passion for building intelligent systems that bring real-world value and improve the way we work. With hands-on experience across the AI development lifecycle, you’re comfortable moving between experimentation and scalable deployment. You enjoy mentoring others, growing engineering talent, and fostering a positive and productive team culture. You stay curious and current with industry trends, and you thrive in an environment where innovation is balanced with delivering impact.
What You’ll Do
As AI Engineering Manager, you will:
- Lead & Grow a cross-functional squad of AI/ML engineers (4–6 people), taking full ownership of their performance, career development, day-to-day coordination and foster an inclusive, collaborative culture.
- Architect & Deliver production-grade AI systems—from prototyping ML features to scalable cloud deployment.
- Lead design of AI solutions (e.g. vector databases to support semantic search, transformers for classification in the scientific domain).
- Own end-to-end pipelines: data ingestion, feature engineering, model training, serving (FastAPI/KubeFlow).
- Partner with MLOps teams to leverage GCP Vertex AI.
- Bridge between Product, Data, MLOps and Research: translate business/user needs into technical roadmaps and ensure timely delivery.
- Hands-On: spend ~30–40% of your time coding and reviewing code, shaping model training pipelines, ML experimentation, and reviewing infrastructure (Docker/K8s).
- Champion Best Practices: enforce code quality, ML lifecycle standards, testing, monitoring and CI/CD for ML.
- Strategic Alignment: Work with product managers to shape the AI roadmap and prioritize experiments. Monitor KPIs (accuracy, latency, cost) and iterate to hit SLAs.
- Innovation & Experimentation: Reserve team time for R&D; encourage proof-of-concepts in ML and GenAI and keep abreast of the latest in NLP, embeddings, vector search and share learnings.
Must-Have Qualifications
- Education: MSc or higher in CS, Engineering, Data Science or related.
- People Management: 3+ years managing AI/ML engineers; strong track record of hiring and developing talent.
- AI/ML Expertise: deep knowledge of ML algorithms, with a focus on NLP and transformers.
- Software /Cloud: 3+ years production experience Python; experience with Docker, Kubernetes, FastAPI; hands-on experience with any major cloud provider (GCP/Azure/AWS)
- MLOps: familiarity with CI/CD for models, monitoring, versioning, pipelines (e.g. KubeFlow)
- Communication: business-fluent English; able to translate complex concepts for diverse stakeholders.
By joining Springer Nature, you will actively contribute to the development and implementation of AI solutions that drive the future of scientific publishing. As a leader, you will guide your team to innovate and grow, pushing the boundaries of what’s possible in AI. Join us as we pioneer the future of scientific publishing through artificial intelligence.
