As an AI DevOps Engineer in the Software & Data Science team, you will program the intelligence behind the chips, transform complex data into actionable insights, and create cutting‑edge solutions that redefine industries and solve tomorrow's challenges.
Your Role- Design and implement CI/CD pipelines for AI/ML models targeted toward chip development, ensuring smooth deployment to production environments.
- Deploy and monitor AI/ML models in production, ensuring they meet performance, scalability, reliability, versioning, and rollback requirements.
- Collaborate with data scientists and engineers to understand model requirements, develop deployment strategies, and ensure seamless integration with existing infrastructure.
- Develop and implement automated testing and validation frameworks to ensure AI/ML models meet quality and performance standards and manage performance drifts.
- Manage and optimize infrastructure resources (compute, storage, networking) to support AI/ML workloads, ensuring efficient use of resources, minimizing costs, and driving continuous improvement.
- Degree in Computer Science, Information Technology or related fields such as Artificial Intelligence, Machine Learning, or Data Science.
- 3+ years of experience in DevOps, software engineering, or a related field.
- Experience working with AI/ML models, CI/CD pipelines, containerization (Docker), cloud-based infrastructure (AWS, GCP, Azure) and container orchestration (Kubernetes).
- Relevant certifications in DevOps, Cloud Computing, or AI/ML engineering (e.g., AWS Certified DevOps Engineer, Google Cloud Certified – Professional Cloud Developer).
- Strong experience with programming (Python, Java), CI/CD tools (Jenkins, GitLab), containerization (Docker, Kubernetes), cloud platforms (AWS, GCP), and automation tools (Ansible).
- Familiarity with AI/ML frameworks (TensorFlow, PyTorch) and monitoring/logging tools (Prometheus, Grafana).
- Fluency in English (mandatory).
Subject to meeting all job requirements, belonging to protected categories under Law 68/99 will be considered a preferential requirement.
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