Senior Advisor, Machine Learning Engineer – Egypt – Information Technology Company – ML-152

Information Technology Company located in Cairo, Egypt looking for Senior Advisor, Machine Learning Engineer with the below requirements:

• 8+ years of related experience with a Bachelor’s degree (or equivalent experience), or 6+ years with a Master’s, or 3+ years with a PhD; Experience to include:
• Software engineering experience in productionizing Machine Learning models, and scaling them in low-latency settings (C, C++, Python)
• Primary experience with object-oriented programming languages such as C# or Java, and with Data Science tools & frameworks and data engineering tools (Python, Spark, Tensorflow, XGBoost…)
• Data Science Platform knowledge – Deep knowledge of machine learning operations and cloud-native ecosystems, information retrieval, data mining, statistics, NLP or related field; Proficient in Data Mining, Data transformation, and Database building ( ETL, SQL OLAP, Teradata, Hadoop )
• Microsoft Azure, AWS, and Google Cloud – must have hands-on experience working on cloud environments to build and deploy models.
• Knowledge of cloud-native computing DevOps, data streaming and extraction, parallelized workloads using Docker, Kubernetes, Test Driven Development, and Continuous Integration / Continuous Deployment.
• Creative Problem-solving approach, and excellent communication skills verbally, in writing, in presentations and meetings, with relationship building and teamwork success based on building trust.
• Deep experience in machine learning and especially building solutions thru Neural networks is a plus.
• Big Data experience in driving real-time analytics.

Responsibilities:

• Build Data Pipelines & Platform to operationalize Machine Learning (ML) models at scale
• Work with the data science team to enable robust decision-making in terms of thinking about scale, latency, and throughput requirements; and create tools/systems to speed up ML lifecycle
• Play a significant role in enabling the adoption of sophisticated algorithms and data mining strategies
• Generate new practices and processes for effective ML engineering, in alignment with core subject-matter expertise
• Define best practices for code optimization, model and system validation, and model governance