MLOps Systems Engineer
4 weeks ago
Job Title: MLOps Specialist
Job Description:
About the Role: We are seeking a highly skilled MLOps Specialist to join our team at Airbus. As an MLOps Specialist, you will play a crucial role in the development and deployment of artificial intelligence and machine learning models.
Key Responsibilities:
- Configure and maintain AI/ML services on dedicated computation nodes or as part of a bigger HPC system to enable internal customers.
- Create and manage MLOps environments to develop concepts for industrialization and maintenance of ML models.
- Develop and implement AI service concepts for future HPC set-ups.
- Design and implement hybrid AI on-prem/cloud services.
- Install, configure, tune, and monitor Linux-based applications in virtual and physical large-scale transnational environments.
- Engage with internal customers to utilize provided resources and gather feedback to improve the MLOps environment.
- Participate in daily scrum meetings of agile and operational teams.
- Act as an intercultural bridge between Europe and India, interacting and exchanging with French, German, or Spanish engineering teams.
- Participate in PI planning workshops every 10-12 weeks.
Requirements:
- Engineering graduate with 5-7 years of experience in engineering software applications.
- Strong understanding of software development, design concepts, and principles.
- Proven track record of building and maintaining applications at scale for end-to-end implementation.
- Strong knowledge of MLOps infrastructure and services, including containerized solutions, orchestration, and scheduling of jobs/ML experiments.
- Good Linux skills, preferably on Redhat 7.x, Redhat 8.x, Redhat 9.x, Centos, and Ubuntu.
- Advanced knowledge of AWS Services, including migration of complex solutions to AWS infrastructure and designing cloud and on-premise solutions architecture.
- Strong knowledge of cloud by design and cybersecurity.
- Deep understanding of coupled, decoupled, and loosely coupled architectures.
- Experience with Continuous Integration and Continuous Deployment processes and tools.
- Experience in setting up hybrid on-prem/cloud solutions, including cloud-enabled schedulers and MLOps environments.
- Knowledge of working/integration with Large Language Processing (LLM) and GCP Gemini.
- Experience in REST API integration within multi-cloud and hybrid environments.
- Experience in building solutions with AWS Sagemaker services and ML Workloads.
- Working experience on Data Platforms, including Databricks, Snowflake, or Palantier.
- Experience in Model Development, model lifecycle management, and deployment.
- Experience with Scientific Compute platforms architecture (HPC, scientific computing workspaces).
- Strong willingness to engage internal AI/ML customers and stakeholders.
- Knowledge of Agile/SAFe principles and Service Management best practices.
- Experience in working with Version One, JIRA, or other equivalent tools for Agile projects.
- Experience in working with ServiceNow or other equivalent tools for incident, problem, and change management.
Success Metrics:
- Agile mindset, collaborative way of working, quick reaction in case of operational issues, SLA fulfillment, and service availability.
- Consistent on-time delivery and quality of projects.
- Innovative cost-effective solutions.
- Customer satisfaction.
- Ability to handle a subject from demand management to development, integration, maintenance, and support.
We are an equal opportunities employer and welcome applications from all qualified candidates.
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