MLOps Systems Engineer

4 weeks ago


Bengaluru, Karnataka, India airbus Full time

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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