Company Description
Company Description RambollRamboll?is a global architecture, engineering, and consultancy company, delivering innovative and sustainable solutions across Buildings, Transport, Energy, Environment & Health, Water, and Management Consulting. With 15,500 experts in 35 countries, we combine local insights with global expertise to shape the society of tomorrow.Inviting Bright MindsAt Ramboll, we empower our people to challenge the status quo and push the boundaries of their profession. Our collaborative and inclusive culture fosters excellence and innovation. Since 1945, we've been committed to leaving a positive impact on societies, companies, and individuals worldwide.At Ramboll Tech, we believe innovation thrives where engineering expertise meets intelligent automation.As a Senior/Lead Machine Learning Engineer, you will shape the future of AI at Ramboll architecting, deploying, and evaluating scalable, responsible, and domain-aware ML and LLM systems that power our next generation of digital products.You will act as a technical leader and architect of AI and agentic systems, defining how these technologies integrate with Ramboll's engineering platform. Collaborating with Product Architects, Data Engineers, and Product Owners, you will deliver intelligent solutions that enable automation, reasoning, and data-driven decision-making across Ramboll's digital ecosystem.Your work will directly influence how Ramboll designs sustainable, AI-enabled products for clients and society.What You Will DoTechnological Leadership & Architecture
- Design and maintain AI and agentic architectures that enable autonomous reasoning, decision support, and knowledge integration across Ramboll's digital platforms.
- Architect and deliver scalable ML, LLM, and multi-agent systems that integrate structured and unstructured data sources.
- Define design principles, standards, and guardrails to ensure technical excellence, reproducibility, and ethical AI development.
- Lead initiatives that embed intelligent automation and reasoning capabilities into engineering workflows.
Evaluation and Observability
- Design and apply robust evaluation frameworks to measure model and agent performance, transparency, and bias.
- Establish metrics and dashboards to monitor quality, latency, sustainability metrics, and cost, identifying and implementing improvements for better outcomes
- Drive adoption of AI observability practices for continuous improvement and compliance.
MLOps and Orchestration
- Develop and optimize automated training, deployment, and monitoring workflows across environments.
- Integrate orchestration principles for multi-agent and retrieval-augmented (RAG) pipelines into CI/CD processes, ensuring scalable, reliable AI delivery.
- Lead by example in implementing sustainable, cost-efficient, and transparent ML operations.
Collaboration and Mentoring
- Partner with Product Architects, Data Engineers, and Chapter Leads to operationalize AI and agentic architectures in digital products.
- Mentor ML Engineers and Developers, fostering growth in system design, evaluation frameworks, and AI lifecycle management.
- Contribute to global AI capability building through knowledge sharing, reusable frameworks, and cross-Pod collaboration.
Qualifications
How You Will Succeed in Your RoleWe're looking for an experienced ML professional who combines deep technical knowledge with collaborative leadership and a passion for responsible innovation.You don't need to meet every qualification if you have the ambition and mindset to grow with us, we'd love to hear from you.Education
