Requirements

Expected technologies

TensorFlow

Pytorch

Docker

Kubernetes

CI/CD

Grafana

Operating system

Windows

Our requirements

● 6+ years of industry experience with a Master's degree or 3+ years of industry experience with a PhD degree.

● Extensive industry experience in low latency, high throughput distributed microservices.

● Extensive experience with machine learning serving system design, architecture, real time monitoring/alerting components (e.g., Prometheus/ Grafana), and distributed cache systems (e.g., Redis/Aerospike).

● Familiarity with CI/CD, ETL, big data tools, and mainstream ML libraries (e.g., MapReduce, Spark, Flink, Kafka, Docker, Kubernetes, TensorFlow, PyTorch, Spark ML, etc.).

● Solid theoretical background in machine learning or data mining and strong conceptual, problem solving, and analytical skills.

● Knowledge on testing frameworks for online A/B testing, canary, blue-green deployment.

● Extensive programming experience in Python, Go or other OOP languages and familiarity with data structures, algorithms and software engineering principles.

● Strong communication and interpersonal skills to drive cross-functional partnerships.

● Ability to work in a fast-paced environment, quickly debug issues, provide proof of concept solutions and apply the changes to production.

Optional

• Knowledge about ML serving technologies, such as Seldon, Triton, ONNX, ONCL, TensorRT.
• Knowledge about Amazon Web Services (AWS).
• Experience with the advertising industry and real-time bidding (RTB) ecosystem.
• Full stack experience with Ruby on Rails and React.

Your responsibilities

● Design and develop highly scalable, real-time machine learning infrastructure with extremely high throughput and low latency conditions, to support the entire advertising business in Samsung.

● Explore and optimize our current machine learning serving system to ensure 5 nines uptime (continuous availability).

● Research the latest machine learning serving technologies and keep up-to-date with industry trends and developments.

● Experiment with new machine learning serving architecture ideas tailored to our environment and create quick prototypes/ proof-of-concepts.

● Collaborate with different internal ML teams (e.g., model engineers, ML platform, and MLOps) to build a world-class ML infra for advertising platform in the industry.

● Closely work with cross-functional partner teams in global settings to deliver new ML features and solutions and achieve business objectives.

● Mentor junior engineers and provide technical guidance.

● Learn quickly and adapt to a fast-paced working environment.