SRE: AML Platform at Scale (Reliability & ML)

SRE: AML Platform at Scale (Reliability & ML)

Full-Time 72000 - 88000 $ / year (est.) On-site
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At a Glance

  • Tasks: Design and maintain scalable ML systems for global AML workloads.
  • Company: Join TikTok's innovative USDS Joint Venture team.
  • Benefits: Competitive salary, flexible work options, and skill development opportunities.
  • Other info: Collaborative environment with opportunities for career growth.
  • Why this job: Make a real impact on TikTok users while enhancing your tech skills.
  • Qualifications: Experience in coding, performance analysis, and large-scale operations.

The predicted salary is between 72000 - 88000 $ per year.

Tik Tok USDS Joint Venture is seeking a Site Reliability Engineer to design, build, and maintain highly available, scalable ML systems supporting AML workloads globally from Australia.

You will sharpen your skills in coding, performance analysis, and large-scale operation while shaping decisions on hardware and capacity.

You will collaborate with software engineers to ensure reliability, security, and performance. Join us to improve platform resilience and impact Tik Tok users worldwide.

SRE: AML Platform at Scale (Reliability & ML) employer: TikTok USDS Joint Venture

At TikTok, we pride ourselves on being an exceptional employer, particularly for the Senior Site Reliability Engineer role within our dynamic Product Engineering team. Our commitment to fostering a collaborative and innovative work culture is complemented by ample opportunities for professional growth and development, ensuring that every team member can thrive in their career. With a focus on diversity and inclusion, as well as a fully in-person work environment that enhances teamwork and agility, TikTok offers a unique and rewarding experience for those looking to make a meaningful impact in the tech industry.

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Contact Details:

TikTok USDS Joint Venture Recruitment Team

We think you need these skills to ace SRE: AML Platform at Scale (Reliability & ML)

Site Reliability Engineering
Machine Learning Systems
Performance Analysis
Scalability
Coding Skills
Collaboration with Software Engineers
Reliability Engineering