| AI/Machine Learning Engineer || Apple || Austin, TX || Hybrid || 12+ months || No H1B and CPT at Austin, Texas, USA |
| Email: [email protected] |
| No H1B and CPT Must be local to Texas Only,, No relocation Job Description Job Title: AI/Machine Learning Engineer Client: Apple Location: Austin, TX Duration: 12+ months Visa: No H1B and CPT Remarks: Candidate MUST relocate to Austin, TX if hired and follow a Hybrid work schedule: 3 days onsite, 2 days remote. Description: 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, and maintain high-standard documentations 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, familiar with Pandas and Numpy 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 REST API development in Python Education Bachelors in computer science or engineering; Masters preferred 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 Education: Bachelors in computer science or engineering; Masters preferred Thanks & Regards Srijan Roy. Technical Recruiter. E-mail: [email protected] Desk No: 980-341-1430, Ext: 1132 LinkedIN: linkedin.com/in/srijan-roy-53541828 -- Keywords: artificial intelligence machine learning information technology Texas |
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| Mon Oct 16 21:49:00 UTC 2023 |