- Location
- Ho Chi Minh City, Ho Chi Minh, Vietnam · published
- Type
- Full-time
- Department
- Engineering
- Source
- Workable
Description
About KNOREX
Founded in 2009, Knorex (https://knorex.com) is a technology company that provides programmatic advertising products and solutions to marketers to connect in real-time to their desired audience worldwide. Through its flagship universal marketing platform, Knorex XPO unifies the connectivity to each of the major marketing channels including social media, search, connected TVs/OTTs, video, audio, display/native, and email, in one place, while simplifying execution and optimization across these channels through AI automation. Knorex operates across the US and APAC.
Job Description
We are seeking MLOps Engineers with the zest and passion to work on our in-house machine learning platform, which covers the whole life-cycle of machine learning, from data collection and augmentation pipeline, to model training and serving, to monitoring and analysis. You will be joining our R&D team working closely with Data Scientists, Research Scientists, and Software Engineers to build a highly scalable system that can handle billions of requests per day, all delivered in milliseconds.
In this role, you will work on large-scale and low-latency ML systems. You need to acquire a deep technical understanding of the platform, work with our cross-country team located regionally to learn about the business and technical analytics requirements, and translate them into production system.
KEY RESPONSIBILITIES
- Plan, design and develop components in the data pipeline to enable various machine learning models in production.
- Work closely with Data Scientists and Research Scientists to translate the state-of-the-art to production systems.
- Develop metrics to measure the outcome/impact of your introduced solutions.
- Investigate the existing pipeline, identify bottlenecks and optimize the throughput and latency of ML components.
- Evaluate and identify new technologies for implementation.
- Communicate with our business and technical teams to understand the analytics requirements.