[xrecnet] Looking for MLOps Consultant @ New York City, NY

Note: Please share me your consultant updated resume to hari.p@itechus.net

 

Hi,

 

Hope you are doing well,

 

Please find the below requirement and if you are comfortable and interested, please share me your updated resume with contact details ASAP. Thanks

 

Role: MLOps Software Engineer

Location: New York City, NY

Duration: 6+ Months Contract 

  

Job Description:

•         3+ years of experience working with data scientists in a large-scale data engineering or production machine learning inferencing capacity, working with various types of supervised and unsupervised learning algorithms for classification, recommendation, anomaly detection, clustering and segmentation, as well as CNNs, RNNs or other deep learning algorithms

•         5+ years of full-stack experience developing large scale distributed systems and multi-tier applications

•         5 years of programming proficiency in, at least, one modern JVM language (e.g. Java, Kotlin, Scala) and at least one other high-level programming language such as Python

•         2+ years of production DevOps experience

•         2+ years of programming on the Apache Spark platform, leveraging both low level RDD and MLlib APIs and the higher-level APIs (SparkContext, DataFrames, DataSets, GraphFrames, SparkSQL, SparkML).  Demonstrated deep understanding of Spark core architecture including physical plans, DAGs, UDFs, job management and resource management

•         At least 1 year of implementation experience with Apache Airflow, and a demonstrated expert level understanding of both segmented and unsegmented Directed Acyclic Graphs and their operationalization

•         Experience working with MLflow and a demonstrated ability to lead architecture efforts for its implementation

•         Demonstrated experience working with inner sourcing initiatives, serving both as a trusted committer and contributor

•         Strong technical collaboration and communication skills

•         Unwavering commitment to coding best practice and a strong proponent of code review

•         Cultural bias towards continual learning, sharing best practice, encouraging and elevating less experienced colleagues as they learn

 

Thanks & Regards

Hari Prasad

Sr. Technical Recruiter

hari.p@itechus.net

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