![Lingaro](https://media.trabajo.org/img/noimg.jpg)
AI Engineering Leader for Cloud Solutions
7 hours ago
Lingaro is a leading company in the field of artificial intelligence and machine learning, with a strong presence in the market since 2008. We have a global team of over 1500 talented individuals across 7 sites, and we are committed to providing a stable and supportive work environment.
Job Description
We are seeking an experienced AI engineering leader to join our team and help us build high-performing, scalable, enterprise-grade ML/AI applications in cloud environments. This is a challenging and rewarding role that requires a deep understanding of AI and ML concepts, as well as experience in designing and implementing data pipelines.
Required Skills and Qualifications
To be successful in this role, you will need to have:
- At least 5 years of experience in a similar position
- Good understanding of ML/AI concepts, including types of algorithms, machine learning frameworks, model efficiency metrics, model life cycle, and AI architectures
- Practical experience in MLOps tools like MLFlow, Azure ML, and/or Databricks
- Good understanding of cloud concepts and architectures, as well as working knowledge of selected cloud services, preferably MS Azure
- Strong experience in at least one of the following domains: Machine Learning, Deep Learning, Data Science, MLOps, Generative AI
- Experience in programming ML algorithms and data processing pipelines using Python
- At least 2 years of experience in production-ready code development
- Practical skills with scripting languages
- Experience in designing and implementing data pipelines
- Good communication skills
- Ability to work in a team and support others
- Taking responsibility for tasks and deliverables
- Great problem-solving skills and critical thinking
- Fluency in written and spoken English
- Good understanding of CI/CD and DevOps concepts, and experience in working with selected tools (preferably GitHub Actions, GitLab, or Azure DevOps) is a plus
- Experience in productizing ML solutions using technologies like Spark/Databricks or Docker/Kubernetes is a plus
Benefits
We offer a comprehensive package of benefits, including:
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