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remoteroles

Staff Software Engineer, ML Infra & Distributed Systems

Tubi Open
Remote San Francisco Toronto Senior ML Platform & Ops

At a glance

Senior ML Platform & Ops role at Tubi. Remote, United States · $227,200–$324,500 base.

SalaryStated by Tubi
$227,200 – $324,500
Base salary for this role, in USD per year, as published in the posting.
This role, from TubiOur estimate for the market: $220,966–$276,675Median $245,000
The range includes the market median of $245,000 for senior ML platform & ops roles in San Francisco, compared against the San Francisco market.
Worked out from 39 postings that stated pay, median $245,000. Last updated Nov 13, 2026.
RoleML Platform & Ops
SenioritySenior
LocationSan Francisco
WorkplaceRemote
Base pay$227,200–$324,500
PostedSep 16, 2025
Also hiring inToronto
Role brief

remoteroles summary, based on the employer's posting.

What you'll do

  • Build high-throughput, low-latency distributed systems in Scala for machine-learning inference
  • Create reusable services for personalization, search, ads and exploration applications
  • Work with ML engineers to solve infrastructure challenges and use measurements to reduce latency, cost and inefficiency
  • Set architecture for ML infrastructure with product and engineering teams, and lead major cross-team refactoring when needed
  • Coach engineers on system design, incident response, interviewing and using LLMs in their work

What you bring

  • You have built scalable distributed systems using a modern backend language
  • You bring strong experience with AWS or a comparable cloud service
  • You have operated low-latency online microservices at scale and handled resolution of several major incidents
  • You have worked with SQL and NoSQL data stores, message brokers, caches and containerization technologies

Who this fits

This staff-level role suits an experienced engineer who can shape infrastructure architecture, lead cross-team work and mentor colleagues. The position is listed as remote and located in San Francisco.

From the employer

About the Role:

As a Staff 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. This role grants the architectural freedom to explore new frameworks, lead critical cross-functional projects, and transform the capabilities of our ML and Product teams.

Responsibilities:

  • Design and build scalable, high throughput, and low latency distributed systems using Scala
  • Build reusable components and services that serve various ML applications like Personalization, Search, Ads and Exploration
  • Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions to address them. Proactively recommend solutions to keep our ML Inference stack state of the art.
  • Take a data driven approach to identifying & optimizing latency, cost, and efficiency of our infra. Lead large scale cross functional refactorings if necessary
  • Mentor other engineers on the team on system design, effective incident management, interviewing, leveraging LLMs for work, etc.
  • Collaborate with ML, Product, and cross functional engineering teams to define the long term vision and architecture for ML Infrastructure at Tubi.

Your Background:

  • Experience designing and building scalable, distributed systems in any modern backend language (e.g., Scala, Java, Python, Go, C++); experience with Scala or JVM based language is a plus.
  • Strong experience with AWS or an equivalent cloud platform
  • Experience building online microservices at scale with low latency serving
  • Experience with both SQL (e.g. Postgres) and NoSQL databases (e.g. Cassandra), message brokers (e.g. Kafka), and caches (e.g. Redis)
  • Experience with containerization technologies, such as Docker or Kubernetes
  • Led the response and resolution efforts for multiple major, large-scale incidents

Bonus:

  • Familiarity with the machine learning infrastructure like inference engines (e.g. torschserve, triton, vLLM), vector stores (e.g. LanceDB, FAISS), feature stores (e.g. Feast), ElastiCache, model training orchestration, etc.
  • Understanding of ML model training pipelines and model internals. Experience with Recommender Systems, Search, Autocomplete and Ads ML is a plus
  • Previous experience with Akka, Erlang, Elixir or Go
  • Proficient in data-driven analysis of complex A/B testing results

About Tubi:

Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

Pursuant to state and local pay disclosure requirements, the pay range for this role, with final offer amount dependent on education, skills, experience, and location is listed annually below. This role is also eligible for an annual discretionary bonus, long-term incentive plan, and various benefits including medical/dental/vision, insurance, a 401(k) plan, paid time off and other benefits in accordance with applicable plan documents.

High cost labor markets such as but not limited to Los Angeles, New York City, and San Francisco$227,200—$324,500 USD

Tubi is a division of Fox Corporation, and the FOX Employee Benefits summarized here, covers the majority of all US employee benefits. The following distinctions below outline the differences between the Tubi and FOX benefits:

  • For US-based non-exempt Tubi employees, the FOX Employee Benefits summary accurately captures the Vacation and Sick Time.
  • For all salaried/exempt employees, in lieu of the FOX Vacation policy, Tubi offers a Flexible Time off Policy to manage all personal matters.
  • For all full-time, regular employees, in lieu of FOX Paid Parental Leave, Tubi offers a generous Parental Leave Program, which allows parents twelve (12) weeks of paid bonding leave within the first year of birth, adoption, surrogacy, or foster placement of a child in addition to applicable government leave program(s) and FOX’s short-term disability policy. This time is 100% paid through a combination of any applicable state, city, and federal leaves and wage-replacement programs in addition to contributions made by Tubi.
  • For all full-time, regular employees, Tubi offers a monthly wellness reimbursement.

About Tubi:

Boldly built for every fandom, Tubi is a free streaming service that entertains over 100 million monthly active users. Tubi offers the world's largest collection of Hollywood movies and TV shows, thousands of creator-led stories and hundreds of Tubi Originals made for the most passionate fans. Headquartered in San Francisco and founded in 2014, Tubi is part of Tubi Media Group, a division of Fox Corporation.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, gender identity, disability, protected veteran status, or any other characteristic protected by law. We will consider for employment qualified applicants with criminal histories consistent with applicable law.

Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

ML Platform & OpsRemote$220k+

Find me work

By the team behind remoteroles.

Find me work
Opportunity

ML Platform & Ops work from LinkedIn, X, Reddit and Upwork, in one list.

Each morning you get everything that fits, strongest first.

Find me work

By the team behind remoteroles.