Original listing text, shown exactly as published by the company.
What you’ll do
- Contribute to the infrastructure supporting AI workflows — training pipelines, Kubernetes deployments and CI/CD.
- Help improve the developer experience for the data science team — small frictions add up, and you’ll help eliminate them.
- Build out and improve observability tooling — learning to see the system clearly is a core skill we’ll develop together.
- Keep deployments clean and correct as the platform evolves.
- Grow into a deeper technical contributor under the mentorship of senior engineers who have done this at high scale.
What we’re looking for
- A genuine, demonstrable depth in Linux — hands-on experience beyond basic usage (for example, debugging, configuration or performance tuning).
- Strong software engineering fundamentals — you write clean code, reason about systems and debug methodically.
- A systems-oriented mindset — you think about why things work, not just that they work.
- Early exposure to reliability concepts — CI/CD, infrastructure-as-code or similar.
- An ownership mindset — especially when diagnosing and resolving production or project issues.
- Comfort using AI tooling to accelerate your work, with the discipline to verify what it produces.
- Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs.
- A track record of critically evaluating and validating AI-assisted work (for example, testing, source checking, data validation, peer review).
- High integrity and ownership: you protect sensitive data, avoid over-reliance on AI and remain accountable for final decisions and deliverables.
- 2+ years of experience building and operating high-performance distributed systems.
- Bachelor’s degree in computer science, engineering, a related field or equivalent experience.
- Nice-to-haves
- Experience with NixOS or other tools for reproducible builds, and an interest in making development environments predictable and reliable.
- Experience with Zig or similar low-level languages, and curiosity about what your compiler and runtime are doing under the hood.
- You’ve reverse-engineered something — a protocol, a binary, a game, etc.
- You’ve deployed something real to Kubernetes, even if it was a homelab.
- Experience with Terraform or other infrastructure-as-code tools in a real context.
- Exposure to adtech, CTV or other high-performance/low-latency environments.
- Python or Scala experience in a data-adjacent context.
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.
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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.
