Senior DevOps Engineer (MLOps)
Project Description DXC is a leading independent IT service provider. In the field of AI and Machine Learning, DXC is recognized as a strong partner for the whole machine learning lifecycle. DXC's MLOps offering provides first class services that help clients to operationalize and to maintain critical machine learning models and applications. Projects in the field of MLOps cover three big domains: Consulting, platform development and operationalization of machine learning models at scale. The candidate will join a cross-functional team of enthusiastic innovators as a Machine Learning Engineer, working for various clients in the field of industrialized Artificial Intelligence. Responsibilities RoleMLOps ArchitectResponsibilities: Participate in requirements gathering, technical specification, and the design and development of complex operationalizing machine learning projects Contribute to architecture design, development of data or machine learning pipelines, and integration into enterprise systems Build and configure multi-tenant machine learning environments on-prem, cloud or hybrid Build, test and optimize Machine Learning models Interact with teams of engineers from multiple disciplinesMandatory skills: Bachelor or master's degree in computer science, natural sciences, mathematics, or equivalent qualification At least one year of professional experience in a similar position or as software developer Experience in Python and ML Experience with at least one CI/CD tool, e. g. Jenkins, Github actions, or cloud equivalents Experience in application containerization and orchestration tools - Docker, Kubernetes, or cloud equivalents Experience with Pipeline Tools, e. g. Kubeflow, Airflow, or cloud equivalents Experience with Model Repositories, e. g. mlflow, modelDB, or cloud equivalents Experience with logging and monitoring, e. g. Prometheus, Grafana, or cloud equivalents Able to communicate and present internally and externally in a confident manner Highly motivated team player, proven ability to lead teams Nice-to-have skills: Experience with Data Versioning, e. g. dvc, pachyderm, or cloud equivalents Experience with ML computing on cloud platforms - preferably Azure or AWS Experience with deployment automation, e. g. Helm, Ansible, Terraform Basic understanding, background in platform administration: Understanding of Linux, SSH keys setup, experience in Linux packages installation Skills Must have Bachelor or Masters degree required in computer science or equivalent qualification Hands-on experience in delivering and leading Data Science and machine learning projects Proven experience in all phases of a Big Data/Analytics project: Concept & design, development, implementation, change and operation Advanced experience in programming (Python, SQL, bash) Experience with Docker, Kubernetes/AKS/EKS/Openshift Experience with DevOps, CI/CD and MLOps automation Experience in cloud architecting and machine learning technologies - Azure/AWS/GCP Experience in designing data management solution architectures Experience in designing machine learning solution architectures Experience in applying ArchiMate and TOGAF Experience with data versioning, pipeline tools and model repositories, e. g. Kubeflow, dvc, mlflow or cloud equivalents Nice to have Strong customer focus, assertiveness and precise method of operation Ability in understanding of architectural dependencies of technologies in the customer's analytic environments Able to communicate and present internally and externally in a confident manner Highly motivated team player, proven ability to lead teams Languages English: B2 Upper Intermediate Seniority Senior
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