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Role Description

tvScientific is looking for a Senior MLOps Engineer! You'll be working with a distributed engineering team on our Connected TV ad-buying platform, as we scale our Machine Learning practice. We’ve cracked the code on optimizing TV ad campaigns. We’re scaling massively and we need your help to make that scale sustainable.

• Scale the decision-making process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
• Improve the developer experience for the data science team
• Upgrade our observability tooling
• Serve as a technical lead and mentor to the team
• Make every deployment smooth as our infrastructure evolves

Qualifications

• Deep understanding of Linux
• Excellent writing skills
• A systems-oriented mindset
• Experience in high-performance software (RTB, HFT, etc.)
• Software engineering experience + reliability (e.g. CI/CD) expertise
• Strong observability instincts

Requirements

• Reverse-engineering experience
• Terraform, EKS, or MLOps experience
• Python, Scala, or Zig experience
• NixOS experience
• Adtech or CTV experience
• Experience deploying a distributed system across multiple clouds
• Experience in hard real-time low-latency (<10 ms) environments

In-Office Requirement Statement

We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.

Relocation Statement

This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

Salary Information

At Pinterest we believe the workplace should be equitable, inclusive, and inspiring for every employee. In an effort to provide greater transparency, we are sharing the base salary range for this position. The position is also eligible for equity. Final salary is based on a number of factors including location, travel, relevant prior experience, or particular skills and expertise.

US based applicants only

$155,584 — $320,320 USD