MLE Senior Architect Principal Architect
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Job Location:
Monthly Salary:
Posted on:
2 hours ago
Vacancies:
1 Vacancy
Job Summary
We are seeking an experienced AI/ML Architect to design lead and implement advanced artificial intelligence and machine learning solutions. The ideal candidate will have deep expertise in machine learning frameworks data pipelines model lifecycle management and cloud-based AI services.
Key Responsibilities: Design end-to-end AI/ML architectures including data ingestion model development training deployment and monitoring. Evaluate and select appropriate ML algorithms frameworks and cloud platforms (e.g. Azure Snowflake). Guide teams in model operationalization (MLOps) versioning and retraining pipelines. Ensure AI/ML solutions align with business goals performance and compliance requirements. Collaborate with cross-functional teams on data strategy governance and AI adoption roadmap. Preferred Qualifications: Strong background in Computer Science Data Science or a related field. 8 years of experience in data science with at least 2 years in a solution architecture role. Proficiency in Python ML libraries and cloud-native services. Experience with large-scale model deployment and performance tuning.
Key Responsibilities: Design end-to-end AI/ML architectures including data ingestion model development training deployment and monitoring. Evaluate and select appropriate ML algorithms frameworks and cloud platforms (e.g. Azure Snowflake). Guide teams in model operationalization (MLOps) versioning and retraining pipelines. Ensure AI/ML solutions align with business goals performance and compliance requirements. Collaborate with cross-functional teams on data strategy governance and AI adoption roadmap. Preferred Qualifications: Strong background in Computer Science Data Science or a related field. 8 years of experience in data science with at least 2 years in a solution architecture role. Proficiency in Python ML libraries and cloud-native services. Experience with large-scale model deployment and performance tuning.
Key Skills
- Kubernetes
- S3
- Google Cloud Platform
- Cassandra
- System Architecture
- Redshift
- AWS
- Cloud Architecture
- NoSQL
- UML
- Kafka
- Distributed Systems
