Machine Learning Engineer - Machine Learning Infrastructure - USDS

is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

The mission of our AML team is to push the next-generation AI infrastructure and recommendation platform for the ads ranking, search ranking, live & ecom ranking in our company. We also drive substantial impact on core businesses of the company. Currently, we are looking for Machine Learning Engineer - Machine Learning Infrastructure to join our team to support and advance that mission.

In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.

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.

Qualifications

Minimum Qualifications

• 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 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
• 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.

Candidates for this position must be legally authorized to work in the United States. This position is not eligible for visa sponsorship or support.

D&I Statement
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.

Accommodation Statement
TikTok is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://shorturl.at/ktJP6

Data Security Statement
This role requires the ability to work with and support systems designed to protect sensitive data and information. As such, this role will be subject to strict national security-related screening.

#LI-DS4

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $137750 - $237500 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.