Machine Learning Solutions Architect

At least 6 years experience as a Machine Learning Engineer, Software Engineer, or Data Engineer 4-year Bachelor's degree in Computer Science or a related field Experience deploying machine learning models in a production setting Expertise in Python, Scala, Java, or another modern programming language Ability to build and operate robust data pipelines Strong working knowledge of SQL and ability to write, debug, and optimize distributed SQL queries Hands-on experience in one or more big data ecosystem products/languages such as Spark, Snowflake, Databricks, etc. Familiarity with multiple data sources (e.g. JMS, Kafka, RDBMS, DWH, MySQL, Oracle, SAP) Systems-level knowledge in network/cloud architecture, operating systems (e.g., Linux), and storage systems (e.g., AWS, Databricks, Cloudera) Production experience in core data technologies (e.g. Spark, HDFS, Snowflake, Databricks, Redshift, & Amazon EMR) Development of APIs and web server applications (e.g. Flask, Django, Spring) Complete software development lifecycle experience Excellent communication and presentation skills

Design and implement data solutions for customer needs, including model inference, retraining, and monitoring. Provide thought leadership on technologies and solution design. Build and operate solutions in production, ensuring performance, security, scalability, and robust data integration. Design and create environments for data scientists. Work within customer systems to extract and place data. Learn and understand customer technology environments. Define deployment approach and infrastructure for models. Demonstrate business value of data by transforming it into actionable insights. Partner with data scientists to ensure solution deployability and maintainability. Create operational testing strategies and validate models. Ensure quality of delivered product.