Azure ML Engineer (100% Remote)

Role: Azure ML Engineer Location: Dallas TX- REMOTE TILL COVID SETTLEDOWN Duration: 12 Months Contract NOTE: Please do look for "Azure Data Factory (ADF), Azure cache for Redis, Azure CI/CD pipeline, Python, Spark, Kafka, ML models Competent ML engineer, who is independent, results driven and is capable of taking business requirements and building out the technologies to take it to production. Big Data ML Engineer with expert level experience in Hadoop ecosystem and real-time analytics tools including PySpark/Scala-Spark/Hive/Hadoop CLI/MapReduce/ Storm/Kafka/Lambda Architecture/Mongo expert with using the larger Hadoop eco system Familiar with job scheduling challenges in Hadoop Experienced in creating and submitting Spark jobs Experience in high performance tuning and scalability Experience in working on real time stream processing technologies like Spark structured streaming, Kafka, FLink + rocksDB Expertise in Python/Spark and their related libraries and frameworks Experienced with Spring Framework and Spring Boot Experience in building training ML pipeline and efforts involved in ML Model deployment Experience in other ML concepts Real time distributed model inferencing pipeline, Champion/Challenger framework, A/B Testing, Model performance Scorecard and assessment, Retraining framework, etc. Unix/Linux expertise; comfortable with Linux operating system and Shell Scripting Working Experience in Redis DB Writing to and from redis very critcal Also exp Azure cache Experience in creating Kubernetes open-source container-orchestration system for automating application deployment, scaling, and management; (Experience in Azure is preferable) Experience in tweaking/using Jenkins, deployment orchestration and/or Kubernetes for CI/CD pipeline Creating/modifying Dockers, microservices and deploying them via Kubernetes PL/SQL, RDBMS background with Oracle/MySQL Familiarity with Cassandra, Mongo preferred. Design, Development, Unit and Integration testing of complex data pipelines and to handle data volumes to derive insights Ability to optimize code to be able to run efficiently with stipulated SLA Excellent problem-solving skills, with attention to detail, focus on quality and timely delivery of assigned tasks Good presentation and communication skills required