Machine Learning Engineer || Work Location is Austin, TX at Austin, Texas, USA |
Email: [email protected] |
From: Khayal Abbas, Scalable- Systems [email protected] Reply to: [email protected] Hi, Please don't share H1B/CPT/OPT/H4 Profiles. Job Title Machine Learning Engineer Technical/Functional Skills Machine Learning, Python, Java,ETL pipelines Roles & Responsibilities We are looking for a core Machine Learning engineer. Summary We are looking for a Machine Learning Engineer, who has hands-on experience in machine learning system development, Cloud computing, backend development and AI/ML. Automate end-to-end ETL/ML pipelines with structural understanding of data products. . Automate, deploy and maintain ML pipelines into existing cloud resources. Work with team members to assist with data-related technical issues and support their data product needs. Work with team members to evaluate and improve existing ML system and models. Required Skills A background in computer science, engineering, mathematics, or similar quantitative field with a minimum of 2 years professional experience Strong Python/Java programming skills Experience in implementing data pipelines using python Experience with workflow scheduling / orchestration such as Kubernetes, Airflow or Oozie Extract Transform Load (ETL) experience using Spark, Kafka, Hadoop, or similar technologies Experience with query APIs using JSON, ProtocolBuffers, or XML Experience with Unix-based command line interface and Bash scripts Optional Skills Experience with computer vision or natural language processing a plus. Database development experience with Relational or MPP/distributed systems such as Oracle/Teradata/Vertica/Hive a plus Data visualization or web development skills a plus Work Location (Remote, if they can work from anywhere or specific location from where associate need to work. If you put specific location then number of profiles received may be less) Austin,TX (Day 1 onsite/3 days in office) Keywords: artificial intelligence machine learning Texas |
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Tue Oct 31 22:56:00 UTC 2023 |