Chief Generative AI Operations Engineer
Remote in Portugal
Generative AI Operations
& 4 others
Choose an option
We are seeking a Chief Generative AI Operations Engineer to lead the creation and upkeep of scalable machine learning infrastructure that supports efficient AI deployment.
In this role, you will work closely with diverse teams to establish reliable MLOps pipelines and infrastructure, empowering data scientists and engineers to transition ML projects from prototypes to production-ready solutions. Join us to drive advanced AI capabilities within the IT Chief Data Office and make a significant impact.
Responsibilities
- Design scalable AI and ML workloads that align with company objectives
- Develop and sustain reproducible machine learning pipelines
- Deploy AI models into production utilizing model serving infrastructures
- Implement monitoring and logging frameworks for AI services observability
- Define infrastructure needs for MLOps pipelines and related components
- Collaborate with infrastructure engineers to facilitate infrastructure deployment
- Mentor and guide team members to encourage best practices and ongoing improvement
- Coordinate activities with cross-functional teams including data scientists and engineers
- Optimize ML workloads to enhance performance and scalability
- Ensure adherence to security protocols and data privacy regulations
- Assess new tools and technologies to improve AI service delivery
- Document system designs and workflows to support knowledge sharing
- Troubleshoot and resolve AI service production issues
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related discipline
- Minimum 7 years’ experience in AI, machine learning, data engineering, software development, or cloud infrastructure
- Strong expertise in Python and familiarity with AI/ML frameworks such as PyTorch, TensorFlow, HuggingFace, or Scikit-learn
- Experience with model inference runtimes like vLLM, MLServe, or Torch Serve
- Proficiency with containerization and orchestration tools including Docker and Kubernetes
- Experience specifying and implementing infrastructure requirements for ML pipelines
- Strong analytical and problem-solving skills with ability to operate within agile, cross-functional teams
- Effective communication and mentoring abilities to support team growth
- English language proficiency at B2 level or higher
Nice to have
- Experience working with cloud platforms such as Azure, AWS, or Google Cloud
- Understanding of Infrastructure as Code (IaC) methodologies
- Familiarity with experiment tracking tools and pipeline orchestration systems