Staff Software Engineer, ML Infra & Distributed Systems

Tubi; United States; On-site; USD 227,200 - 417,000; Full time

Benefits offered by this job

Flexible Time Off

Parental Leave Program

Wellness reimbursement

Job summary

Tubi is looking for a Software Engineer for its ML Infrastructure team in the United States. This role involves designing and building scalable distributed systems and mentoring team members. Candidates should have experience with cloud platforms like AWS, microservices, and be proficient in modern backend languages such as Scala, Java, or Python. The role offers competitive salaries ranging from $227,200 to $417,000 and various benefits, including flexible time off and parental leave.

Qualifications

• Experience with large-scale cloud systems in modern backend languages.
• Strong knowledge of AWS or equivalent cloud platforms.
• Experience with microservices architecture.
• Familiarity with messaging and caching solutions.

Responsibilities

• Design and build scalable, high-throughput distributed systems.
• Build reusable components for ML applications.
• Collaborate with ML engineers to optimize ML Inference.
• Mentor engineers on system design and incident management.
• Define long-term vision for ML Infrastructure with teams.

Skills

Experience designing and building scalable systems

Strong experience with AWS

Low-latency serving experience

Experience with SQL and NoSQL databases

Containerization technologies (Docker, Kubernetes)

Incident response and resolution

Tools

Kafka

Postgres

Redis

Java

Python

Job description

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 that power essential services such as personalized recommendations, search, and content understanding across Tubi.

Open Positions

• Staff Software Engineer
• Principal Software Engineer
  • Additional Details: As a Principal Engineer on the ML Infrastructure team, you will be a technical leader and visionary, driving the evolution of our machine learning platform. You will tackle the most complex and impactful technical challenges, shaping the architecture and technology choices that enable our ML capabilities to scale and deliver exceptional user experiences. You will be a key influencer, bridging the gap between engineering and product, and a mentor to senior engineers, fostering a culture of technical excellence and continuous improvement. Your work will be used by millions of users.

Responsibilities

• Design and build scalable, high‑throughput, and low‑latency distributed systems using Scala.
• Build reusable components and services that serve various ML applications such as Personalization, Search, Ads, and Exploration.
• Partner closely with ML engineers to understand their challenges and limitations and develop scalable solutions. Proactively recommend solutions to keep our ML Inference stack state of the art.
• Take a data‑driven approach to identifying and optimizing latency, cost, and efficiency of our infrastructure. 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 machine learning infrastructure such as 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, offering the world’s largest collection of Hollywood movies and TV shows, thousands of creator‑led stories, and hundreds of Tubi Originals made for 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—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 Los Angeles, New York City, and San Francisco.

$227,200–$417,000 USD

Benefits

• For US‑based non‑exempt Tubi employees, the FOX Employee Benefits summary accurately captures Vacation and Sick Time.
• For all salaried/exempt employees, Tubi offers a Flexible Time off Policy in lieu of the FOX Vacation policy.
• For all full‑time, regular employees, Tubi offers a generous Parental Leave Program allowing 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 programs and the FOX short‑term disability policy.
• For all full‑time, regular employees, Tubi offers a monthly wellness reimbursement.

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 qualified applicants with criminal histories consistent with applicable law.