Machine Learning Engineer – Machine Learning Infrastructure
| Company | ByteDance |
|---|---|
| Location | Seattle, WA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Mid Level, Senior |
Requirements
- Proficient in at least one programming language such as Go/Python in Linux environment, with excellent coding skills.
- Familiar with open source distributed scheduling/orchestration/storage frameworks, such as Kubernetes (K8S), Yarn (Flink, MapReduce), Mesos, Celery, HDFS, Redis, S3, etc., with rich practical experience in machine learning system development.
- Master the principle of distributed systems and participate in the design, development and maintenance of large-scale distributed systems.
- Possess excellent logical analysis ability, able to perform reasonable abstraction and decomposition of business logic.
- Have a strong sense of responsibility, good learning ability, communication ability and self-motivation, and be able to respond and act quickly.
- Have good working document habits, and write and update work flow and technical documents in a timely manner as required.
Responsibilities
- Responsible for the design and implementation of a global-scale machine learning system for feeds, ads and search ranking models.
- Responsible for improving use-ability and flexibility of the machine learning infrastructure.
- Responsible for improving the workflow of model training and serving, data pipelines, storage system and resource management for multi-tenancy machine learning systems.
- Responsible for designing and developing key components of ML infrastructure and mentoring interns.
Preferred Qualifications
- Experience contributing to an open sourced machine learning framework (TensorFlow/PyTorch).
- Experience in big data frameworks (e.g., Spark/Hadoop/Flink), experience in resource management and task scheduling for large scale distributed systems.
- Experience in using/designing open-source machine learning lifecycle management systems: TFX