Engineer: machine learning iii
Summary
Build and deploy ML models using Python, TensorFlow/PyTorch, and cloud tools; maintain pipelines, services, and infrastructure in an agile team.
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. 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, Num Py, scikit-learn, Tensor Flow, 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 with No SQL 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 Data science life cycle Machine learning concepts Machine learning model life cycle
Ideal: Data Science lifecycle Big data storage and processing solutions Machine learning model architectures
Skills: Analytical Skills Planning, organising and coordination skills #J-18808-Ljbffr