
AI Lead Engineer
- Eindhoven, Noord-Brabant
- € 6.000-7.500 per maand
- Vast
- Voltijds
- 1 dagen geleden geplaatst
- Vacature nummer: V-20049127
- Mentor 30+ engineers across 6 AI focused teams, lead the design, development, and maintainability through CI/CD of scalable AI/ML workloads across hybrid cloud environments
- Design and implement API's to securely expose platform services (ex. AI models) and to integrate loosely coupled application components
- Automate infrastructure provisioning using Infrastructure-as-Code (IaC) tools like Terraform or Ansible. Implement testing of automated deployments and observability frameworks (ex. Prometheus, Grafana, or Datadog) for application functionality including monitoring, logging, and tracing
- Coach colleagues (across ASML regions, ex. US, Veldhoven) in developing solutions in line with industry best practices and 'socialize' generalized frameworks to standardize development. Responsible for quality reviews, guiding cross sector co-development initiatives and continuous improvement.
- Challenging assignments where you can make an impact and fully leverage your technical expertise.
- Personal guidance from both your consultant and the YER back office, ensuring you always have the right support.
- Growth and development opportunities, including participation in the YER Talent Development Programme with your own dedicated coach.
- International support such as Dutch language lessons, assistance with taxes, and housing guidance-helping you feel at home quickly.
- An open and collaborative culture focused on teamwork, results, and knowledge sharing.
- Networking opportunities with other tech professionals from leading multinationals.
- Inspiring events and masterclasses featuring renowned speakers and top companies.
- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
- 8+ years of experience in DevOps, Cloud Engineering, or Site Reliability Engineering, with a focus on AI/ML.
- Strong expertise in cloud platforms (Azure, Google Cloud, or AWS) and Kubernetes (both SDLC on Kubernetes and Kubernetes core underlying components)
- Experience with GPU-accelerated compute environments and AI-specific tools like NVIDIA Triton, Kubeflow, or MLflow.
- Strong software engineering expertise in MLOps practices and proficiency in scripting (Python, JavaScript, Bash, or equivalent).
- Strong hands-on experience with Infrastructure-as-Code (IaC) frameworks like Terraform