Sr. ML Ops Engineer, tvScientific · tvScientific

Sat, 18 Apr 2026 15:55:03 GMT
Engineering

tvScientific · San Francisco, CA, US; Remote, US · $155,584-$320,320 USD · remote

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