Senior AI Engineer
Core
Partner with Data Science and Business teams to develop, operationalize, integrate, and scale algorithmic products and data models.
Role type
Senior AI Engineer (MLOps & Cloud Infrastructure)
Builds
Algorithmic products, ETL/ELT pipelines, distributed computer architectures, and cloud-native AI solutions.
Domain
Data & Analytics, Cloud Infrastructure (Azure/GCP)
Deliverable
production ML models
Required skills
Python, SQL, Data Modeling, ETL/ELT, Cloud Architecture, DevOps, CI/CD, Terraform, Ansible, Azure, Databricks, Logging/Monitoring
Preferred skills
None stated
Technologies
Azure (Databricks, Azure ML, AKS, ADF), GCP (Composer, BigQuery, GKE, Kubeflow), GitHub Actions, Jira, Sonarqube, Logstash, Grafana, Kibana
Responsibilities
Engage in proof of concepts and experiments to evaluate new models; Develop high quality, standard-compliant, tested code; Contribute code and tools to central re-usable libraries; Develop data models, model features, data quality tests, ETL/ELT pipelines, and distributed computer architectures; Deploy algorithmic products across clouds leveraging cloud-native services; Operationalize Machine Learning models as integral element of IT solutions; Troubleshoot infrastructure related issues; Implement best Platform Engineering practices; Coach/teach others on DevOps best practices.
Seniority
Senior, hands-on IC
