tvScientific
51 - 200 employees
Founded 2020
📱 Media
☁️ SaaS
🤝 B2B
Media • SaaS • B2B
tvScientific is a performance-focused Connected TV (CTV) advertising platform that uses AI-powered optimization to deliver measurable business outcomes like installs, sales, and traffic. The platform provides inventory access, targeting, creative management, measurement & attribution, and real-time reporting with a unified dashboard and transparent analytics. tvScientific positions itself as a pay-for-performance solution for consumer brands, offering guaranteed outcomes, brand safety controls, and integrations for scale.
Senior ML Ops Engineer
Job not on LinkedIn
🕒 February 27
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tvScientific
51 - 200 employees
Founded 2020
📱 Media
☁️ SaaS
🤝 B2B
Media • SaaS • B2B
tvScientific is a performance-focused Connected TV (CTV) advertising platform that uses AI-powered optimization to deliver measurable business outcomes like installs, sales, and traffic. The platform provides inventory access, targeting, creative management, measurement & attribution, and real-time reporting with a unified dashboard and transparent analytics. tvScientific positions itself as a pay-for-performance solution for consumer brands, offering guaranteed outcomes, brand safety controls, and integrations for scale.
📋 Description
• Scale the decisionmaking 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.
🎯 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 • 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
🏖️ Benefits
• Information regarding the culture at Pinterest and benefits available for this position can be found here.
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