Back to SearchLead Generative AI Operations Engineer
Remote in Portugal
Generative AI Operations
& 4 others
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We are seeking a Lead Generative AI Operations Engineer to architect and sustain a robust ML infrastructure that supports seamless AI deployment.
In this role, you will work cross-functionally to develop scalable MLOps pipelines and infrastructure, enabling data scientists and engineers to transition ML projects from prototype stages to production environments. Join us to make a significant impact on AI services within the IT Chief Data Office.
Responsibilities
- Design scalable AI and machine learning workloads that align with company objectives
- Develop and uphold reproducible machine learning pipelines
- Deploy AI models into production using model serving infrastructures
- Implement monitoring and logging frameworks for AI service observability
- Define infrastructure needs for MLOps pipelines and related components
- Collaborate with infrastructure engineers to facilitate infrastructure deployment
- Guide and mentor team members to encourage best practices and ongoing improvement
- Coordinate efforts with cross-functional teams including data scientists and engineers
- Optimize machine learning workloads for enhanced 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 for knowledge dissemination
- Diagnose and resolve production issues affecting AI services
Requirements
- Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or a related discipline
- Over 5 years of experience in AI, machine learning, data engineering, software development, or cloud infrastructure
- Strong expertise in Python and proficiency with AI/ML frameworks such as PyTorch, TensorFlow, HuggingFace, or Scikit-learn
- Experience with model inference runtimes including vLLM, MLServe, or Torch Serve
- Proficiency in containerization and orchestration technologies such as Docker and Kubernetes
- Experience specifying and implementing infrastructure requirements for ML pipelines
- Strong analytical and problem-solving capabilities with experience in agile cross-disciplinary teams
- Effective communication and mentoring abilities to support team growth
- English language proficiency at B2 level or higher
Nice to have
- Familiarity with cloud platforms like Azure, AWS, or Google Cloud
- Understanding of Infrastructure as Code (IaC) methodologies
- Experience with experiment tracking systems and pipeline orchestration tools