ML Platform Engineer, tvScientific
About The Position
Millions of people around the world come to Pinterest's platform to find creative ideas, dream about new possibilities, and plan for memories. Pinterest's mission is to bring everyone the inspiration to create a life they love, leveraging AI as a powerful partner to augment creativity and amplify impact. The company seeks candidates excited to be part of this, emphasizing foundational skills and collaboration with AI, and the ability to explain their approach and thinking during the interview process. tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. It uses massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes, combining media buying, optimization, measurement, and attribution in one efficient platform. The platform was built by industry leaders in programmatic advertising, digital media, and ad verification. This role is for an ambitious Systems / Platform Engineer to join a team at the intersection of SRE and low-latency distributed systems. This team will power Pinterest’s next generation of real-time ML and measurement infrastructure, focusing on sub-millisecond decisioning, high-throughput data access, and tight integration with Pinterest’s core tech stack. The engineer will think about queries and RPCs in terms of syscalls, cache lines, and wire formats, designing systems that remain fast and predictable under load. They will help define and harden the foundation for the training and serving stack, covering storage and indexing strategies, streaming and fanout, backpressure, and failure handling across services and regions. Close collaboration with software engineering, data infra, and SRE partners is essential to ensure systems are observable, debuggable, and operable in production. The role offers a chance to apply expertise in areas like IO scheduling and batching, lock-free or low-contention data structures, connection pooling, query planning, kernel and network tuning, on-disk layout and indexing, circuit-breaking, autoscaling, incident response, NixOS, Rust, and robust SLIs/SLOs to business-critical, high-leverage infrastructure at Pinterest scale.
Requirements
- 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
Responsibilities
- 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
- Make every deployment smooth as our infrastructure evolves.
Benefits
- Information regarding the culture at Pinterest and benefits available for this position can be found here.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
No Education Listed
Number of Employees
501-1,000 employees
