Machine Learning Data Associate
KeySkills
Company Name
Job Description
- Job description
- Amazon is a global leader in e-commerce and cloud computing, headquartered in Seattle, Washington. Since its inception in 1995, Amazon has strived to be the worlds most customer-centric company, catering to a global customer base, which includes not only consumers but also our sellers and vendors (selling partners). Our platform empowers world-class retail brands and individual sellers to increase sales and reach new customers.
- The North America Customer Fulfillment (NACF) team is dedicated to effectively network labor planning for optimizing customer experience and enhancing productivity. The successful execution of the network depends on we'll-defined roles and responsibilities. The AI Ops MLDA (Machine Learning Data Associate) team is dedicated to implementing GenAI solutions to automate and augment tasks across North America Supply Chain (NASC) and Global Services Risk & Compliance (GSRC) teams. The team focuses on expanding use-case portfolios and accelerating the automation lifecycle through internal GenAI products for workflow automation.
Job Details
Experience :
1 To 6
Number Of
Vacancies :
5
Job Type :
Permanent
Industry Type : IT/Software
Salary
:
3 Lac - 8 Lac
P.A
Education Summary
UG :
Any UG Degree
PG :
Any PG Degree
Contact Details
Contact
Person :
NA
Contact
Number :
4430883088
e-mailId :
melwintp@amazon.com
Address :
Amazon Development Centre (India) Pvt Ltd,
#40, 3rd Floor, SP InfocityM G R Salai,Perungudi, Kandanchavady,
Chennai.
Office Location
Central Jakarta No 1234, Jakarta, IndonesiaData Engineer Alexa AI Developer Tech
Experience -
3 to 8
Machine Learning Data Associate
Experience -
1 to 6
Developer
Experience -
3 to 5
Key Skills -
Software Development Life Cycle (SDLC),
Programming and Coding,
Software Design and Architecture,
Debugging and Troubleshooting,
Code Optimization,
Version Control (Git),
Testing and,
Quality Assurance,
System Integration,
Process Automation,
Technical Documentation,
Root Cause Analysis,
Requirement Analysis,
System Performance Analysis,
Critical Thinking,
Attention to Detail,
Team Collaboration,
Client Communication,
Customer Focus,
Time Management,
Professional Etiquette,
Agile and Scrum Methodologies,
Performance Tuning,
Database Management (SQL/NoSQL),
DevOps and CI/CD,
Cloud Computing (AWS/Azure/GCP),