[Hiring] Senior Software Engineer, ML Platform @Pinterest

Role Description

We are looking for an experienced ML Platform Engineer to join a team at the intersection of sysops, systems programming, architecture, and large-scale deployments. Our platform underpins tvScientific’s distributed real-time bidding agent and ML training system that together drive $100M+ in annual revenue, giving you the opportunity to work on some of the most business-critical infrastructure in the company.

As part of our team, you’ll think about datasets in terms of bytes, microseconds, and serialization formats, and help define the next generation of our training and serving stack. A flagship initiative for the coming year is building a Kubernetes + Ray backend for our model training pipelines, setting a new bar for scale and reliability. If topics like data locality, observability and anomaly detection, distributed databases, high-performance computing, array programming languages, data security, and reproducibility excite you (even if it’s just a subset), your expertise could play a key role in shaping tvScientific’s ML innovation in 2026 and beyond.

What You'll Do

• 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
• Demonstrated ability to use AI to improve speed and quality in your day-to-day workflow for relevant outputs
• Strong track record of critical evaluation and verification of AI-assisted work (e.g., 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

Nice-To-Haves

• 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.