Senior Data Engineer I

Qualifications • Masters degree in Software Engineering, Data Engineering, Computer Science or related field • 5 years of relevant work experience • Strong Scala and Python background • Experience with Apache Spark and/or Ray • Knowledge of AWS, GCP, Azure, or other cloud platform • Knowledge of current principles and frameworks for ML Ops • Experience with ML Ops technologies such as ML Flow, DVC, Grafana, DataHub, Databricks • Experience with machine learning technologies such as PyTorch, TensorFlow, AWS Sagemaker • Experience with CI/CD pipelines, including Jenkins or Git Actions • Experience with Docker containerization or Kubernetes orchestration • Experience in improving data security and privacy, and managing and reducing cloud costs • Knowledge of API development and machine learning deployment Responsibilities • Develop and implement a strategy for continuous improvement of our Machine Learning Ops including versioning, testing, automation, reproducibility, deployment, monitoring, and data privacy • Develop and report on ML Ops metrics such as deployment frequency, lead time for changes, mean time to restore, and change failure rate • Collaborate with data scientists, data engineers, API engineers, and the dev ops team • Build scalable data ingestion and machine learning inference pipelines • Scale up production systems to handle increased demand from new products, features, and users • Provide visibility into the health of our data platform (comprehensive view of data flow, resources usage, data lineage, etc) and optimize cloud costs • Automate and handle the life-cycle of the systems and platforms that process our data #J-18808-Ljbffr