Sr. ML Ops Engineer, tvScientific

We're looking for a Senior MLOps Engineer to join our distributed engineering team on our Connected TV ad-buying platform. As a Senior MLOps Engineer, you will be responsible for scaling the decision-making process for tools for the tvScientific AI team, improving the developer experience for the data science team, upgrading our observability tooling, serving as a technical lead and mentor to the team, and making every deployment smooth as our infrastructure evolves.

Key responsibilities include:

• Scaling the decision-making process for tools for the tvScientific AI team, from our workflows to our training infrastructure to our Kubernetes deployments
• Improving the developer experience for the data science team
• Upgrading our observability tooling
• Serving as a technical lead and mentor to the team
• Making every deployment smooth as our infrastructure evolves

Requirements include:

• 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 include:

• 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