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TikTok · 2 weeks ago

Software Engineer - Machine Learning Infrastructure - USDS

Seattle, WA

Full-time

Onsite

Mid Level

$178K/yr - $342K/yr

TikTok is the leading destination for short-form mobile video, and they are seeking a Machine Learning Engineer to join their AML team to enhance their AI infrastructure for ads and search ranking. The role involves designing and implementing a global-scale machine learning system, improving infrastructure usability, and mentoring interns.

Content CreatorsContent DiscoveryMedia and EntertainmentSocial MediaVideo

No H1B

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

Qualification

Machine LearningDistributed SystemsProgramming (Go/Python)KubernetesBig Data FrameworksOpen Source ContributionsCommunication SkillsProblem SolvingDocumentation Skills

Required

Bachelor's/Master's degree in Computer Science, Computer Engineering, or related fields or equivalent years of experience in a software engineering role

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

Experience in developing and deploying large-scale systems

Preferred

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

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