Remuneration
Not specified
Location
Spain
Visa sponsorship
Not specified
Job summary
The Senior MLOps Engineer is responsible for operationalizing machine learning models by designing, developing, deploying, and maintaining AWS and Kubernetes-based infrastructure. Key responsibilities include leading MLOps projects, managing CI/CD pipelines, and collaborating with Data Scientists to ensure reliable model operations and performance testing.
Qualifications
- 7+ years engineering experience
- Deep software and cloud knowledge
- Experience in production architecture and API design
- Comprehensive MLOps background
- Hands-on AWS and Kubernetes operations
- Experience in CI/CD pipeline ownership
- Proven ML model service deployment experience
- Hands-on MLflow and Kubeflow experience
- Familiarity with ML frameworks
- Cross-functional collaboration skills
- Project leadership experience
- Mentorship experience
- Strong communication skills
- Problem-solving and critical thinking abilities
- Enthusiasm for knowledge sharing
- Interest in cybersecurity
Responsibilities
- Lead complex MLOps projects
- Design and develop software
- Operate production ML services
- Build and maintain Kubernetes and AWS architecture
- Develop and maintain CI/CD and IaC workflows
- Create and maintain APIs and orchestration layers
- Collaborate with Data Scientists on model production
- Conduct benchmarking and performance testing
- Establish operational standards
- Enhance MLflow and Kubeflow operations
- Evaluate new technologies
- Enforce engineering standards
- Mentor team members
- Collaborate on development roadmaps
- Engage with cross-functional teams
- Share MLOps expertise
- Stay current in MLOps technologies
- Develop cybersecurity domain expertise
- Write technical documentation
Skills
Argo CDAWSC++DockerIAMJavaJenkinsKubernetesPython
Relocation
No