About
Bachelor's degree in Computer Science, Information Systems, or related field; or 8 years of equivalent work experience 3-4 years of additional work experience beyond degree requirements Machine Learning (ML) and Deep Learning (DL):
Proficiency in geospatial and computer vision analysis. Experience with ML/DL models/algorithms (classification, regression, NLP, computer vision). Knowledge of secure AI architectural patterns. Programming Skills:
Proficiency in Python (and PySpark preferred). SQL expertise for data querying and manipulation. Familiarity with Docker and MLOps practices. Cloud Platforms (AWS and Azure):
Experience with AWS services for data engineering (e.g., S3, Glue, Redshift, Lambda). Familiarity with transitioning platforms from Azure to AWS. Data Engineering:
Building and optimizing data pipelines (ETL/ELT processes). Experience with large-scale data ingestion and transformation. Experience with Agile methodologies
Nice-to-have skills
- AWS
- Azure
- Classification
- Deep Learning
- Machine Learning
- Python
Work experience
- Data Engineer
- Machine Learning
Languages
- English
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