Sr. Software Engineer, ML Platform, tvScientific

Pinterest
relocation assistance
United States, California, San Francisco
505 Brannan Street (Show on map)
May 26, 2026
About Pinterest: Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we're on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product. Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other's unique experiences and embrace theflexibility to do your best work. Creating a career you love? It's Possible. At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we're looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we'll explore your foundational skills and how you collaborate with AI. Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here. About tvScientific tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business. We build the infrastructure that powers real-time bidding at scale for Connected TV. Our AI team moves fast, and the platform underneath it needs to be rock-solid, deeply observable and genuinely enjoyable to work in. This role sits at the intersection of systems engineering and ML infrastructure - you'll be a technical lead and hands-on contributor keeping the whole machine running and improving. What you'll do Own the infrastructure that supports AI model training, deployment and serving - from Kubernetes clusters to CI/CD pipelines. Co-architect our next-generation data processing pipeline for reliability, robustness and observability. Drive developer experience improvements for the data science team, building direct relationships with the people you're unblocking. Build and refine observability across the stack so we can detect, debug and resolve issues quickly. Evolve our tooling and workflows as the system grows, with care for correctness and performance at every layer. What we're looking for Linux systems knowledge - beyond surface level, with experience digging into behavior, configuration or source. Strong software engineering fundamentals paired with reliability/platform engineering experience (for example, CI/CD, infrastructure-as-code, distributed systems). Experience working in high-performance environments such as RTB, HFT, hard real-time systems or similar. Strong observability skills - you build and use dashboards, alerts and traces to understand complex systems. A systems-oriented mindset that spans multiple layers of the stack. An ownership mindset and high integrity: you're accountable for what ships and you protect sensitive data. Experience in mentoring other engineers on the team and leading projects, and helping set the technical bar for the team. 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). 4+ 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 Reverse-engineering experience (for example, protocols, binaries or hypervisors). Experience with NixOS or other tools for reproducible builds and system configuration. Experience with Zig or similar low-level languages, and curiosity about what your compiler and runtime are doing under the hood. Experience working with large-scale data systems. Terraform, EKS or other MLOps tooling in production. Exposure to adtech, CTV or other high-performance/low-latency environments. Experience deploying distributed systems in multi-cloud environments. Experience with sub-10ms hard real-time systems. 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 ourPinFlexpage to learn more about our working model. #LI-SM4 #LI-REMOTE 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. Information regarding the culture at Pinterest and benefits available for this position can be found here. US based applicants only $155,584 — $320,320 USD Our Commitment to Inclusion: Pinterest is an equal opportunity employer and makes employment decisions on the basis of merit. We want to have the best qualified people in every job. All qualified applicants will receive consideration for employment without regard to race, color, ancestry, national origin, religion or religious creed, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, age, marital status, status as a protected veteran, physical or mental disability, medical condition, genetic information or characteristics (or those of a family member) or any other consideration made unlawful by applicable federal, state or local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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