Engineer: Machine Learning III

Qualifications and experience: 4 to 6 years Machine Learning and Software Engineering experience Strong analytical and problem-solving skills Expert in Python and SQL Experience with modern software development best practices, e.g. Agile software development Code reviews Unit testing Version control, e.g. git CI/CD Experience with microservice architectures Experience working in an agile team Experience with ML frameworks and tools (e.g. pandas, NumPy, scikit-learn, TensorFlow, Pytorch, Spark MLlib) Experience with modern ETL, compute and orchestration frameworks, e.g. Apache Spark, Apache Flink, Apache Kafka, etc. Development experience in both Windows and Linux Experience with container technologies, e.g. Docker, Kubernetes Experience in building machine learning or AI systems Proficiency in R language Experience deploying models to production Experience building distributed systems Experience with NoSQL databases Experience working with ML platforms, e.g. MLflow, Kubeflow, etc. Experience working with Data Science platforms, e.g. Dataiku, Domino, etc. Experience with cloud-based infrastructure, e.g. Azure, AWS, GCP; (AWS preferred) A relevant degree in Information Technology - Computer Science or Engineering Other A relevant degree in Information Technology - Computer Science or Engineering - Other Knowledge of: Object oriented and functional programming in Python Modern software development practices Database querying using SQL Data science life cycle Machine learning concepts Machine learning model life cycle Microservice architectures Ideal: Data Science lifecycle Distributed system design Big data storage and processing solutions Machine learning model architectures Skills: Analytical Skills Decision making skills Planning, organising and coordination skills Problem solving skills Researching skills Originally posted on Himalayas