Machine Learning Engineer

Your tasks:

• Work with Head of Data Science Team to define the ML models to implement
• Create and maintain ML model training/prediction pipelines in production
• Monitor and provide support to our infrastructure and production models
• Create re-usable tools and frameworks for ML model deployment and monitoring
• Implement cutting-edge, big-data frameworks to support batch and real-time jobs
• Identify possible bottlenecks in the system and perform optimizations

You are the right person for this job if you have...

• Experience working with ML model training/deployment tools such as Airflow, Kubeflow, Seldon…
• Experience in infrastructure, including Cloud Computing, Linux OS, Docker, RDBMS and NoSQL Databases
• Experience working with open source ML libraries such as Tensorflow, PyTorch and XGBoost…
• Experience with large-scale systems in data science, and building production ML pipelines for model training / prediction

You have

• Level of education: Master's degree (recommended but not required) in Computer Science or Big Data Engineering
• 2 years of relevant experience in related fields
• Self-motivated, independent learner, and enjoy sharing knowledge with team members
• Mandatory skills:Familiarity with big data engineering tools such as Spark, Kafka, Google cloud…
• Skills we are looking for in addition,knowledge of any programming language (Python)
• Tools to master: Asana, G-Suite