Software Engineer, ML Infra & Distributed Systems (Staff & Principal)
San FranciscoRemote (US)principal
via Greenhouse
About this role
About the Role:
As a Software Engineer on the ML Infrastructure team, you will collaborate closely with the Machine Learning and Product teams to build world-class machine learning inference platforms. These platforms power essential services like personalized recommendations, search, and content understanding across Tubi.
A core responsibility of this team is developing and maintaining low-latency ML model serving systems that support Deep Learning, LLM, and Search models. This involves building self-service infrastructure and critical components such as the inference engine, feature store, vector store, and experimentation engine.
You will improve the way we deploy and operate our services and even contribute to open-source projects.…
What we'd score you on
reqspace match rubricFive dimensions, recruiter-grade. Upload your resume and we'll generate a written explanation of where you fit and where the gaps are.
1
Skills match
For this role: python, java, go, c++, scala…
2
Level fit
This role is principal-level. We check your trajectory against it.
3
Domain experience
Your work in the role's domain matters more than your years total. We weight recent and direct experience.
4
Recency
A skill you used last quarter weighs more than one from five years ago. We grade on recency, not lifetime.
5
Location fit
This role is remote-eligible — we factor in your stated location and time-zone overlap.
Score yourself on this role.
Free · no card · written explanation included
Skills in this role
Pulled from the job description. These are the keywords we'll weight when scoring your fit.
pythonjavagoc++scalaelixirerlangsqlpostgrescassandraredisawskubernetesdockerkafkateams
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