| Hiring for Machine Learning Engineer in Sunnyvale, CA / Austin, TX (Onsite) at Sunnyvale, California, USA |
| Email: [email protected] |
| Hi, Greetings for the day. I am reaching out to you regarding a job opportunity with one of our clients. Let me know your thoughts. Role: Machine Learning Engineer Location: Sunnyvale, CA / Austin, TX (Onsite) Duration: 12 Months 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. Candidate must have strong NLP exp. 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, Protocol Buffers, or XML Experience with Unix-based command line interface and Bash scripts 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 Thank you & Regards Saikumar Pasunoori Flexon Technologies Inc. (510) 327 5070 [email protected] www.flexontechnologies.com The measure of who we are is what we do with what we have. Keywords: artificial intelligence machine learning access management California Texas Hiring for Machine Learning Engineer in Sunnyvale, CA / Austin, TX (Onsite) [email protected] |
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| Fri Oct 18 19:30:00 UTC 2024 |