Senior Software Engineer, Machine Learning Infrastructure
Tubi
Join Tubi (www.tubi.tv), Fox Corporation's premium ad-supported video-on-demand (AVOD) streaming service leading the charge in making entertainment accessible to all. With over 50,000 movies and television shows, including a growing library of Tubi Originals, 200+ local and live news and sports channels, and 455 entertainment partners featuring content from every major Hollywood studio, Tubi gives entertainment fans an easy way to discover new content that is available completely free. Tubi's library has something for every member of our diverse audience, and we're committed to building a workforce that reflects that diversity. We're looking for great people who are creative thinkers, self-motivators, and impact-makers looking to help shape the future of streaming.
About the Role:
This Software Engineering team works closely with Machine Learning and Product teams to assist in building world-class machine-learning operating systems for the Tubi platform. The efforts of this team help take inference systems to the next level of low latency serving by exploring new frameworks. You will improve the way we deploy and operate our services and even contribute to open-source projects.
Responsibilities:
- Design and build scalable, high throughput, and/or low latency distributed systems using Scala
- You will redesign aspects of the online feature store for efficiency and low latency
- You will work with ML engineers to understand their challenges and limitations and work to solve them
Requirements:
- 5+ years of experience designing and developing scalable distributed systems with either Scala or Java (we use Scala).
- 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)
- Experience with containerization technologies, such as Docker or Kubernetes
Bonus:
- Familiarity with the machine learning infrastructure
- Previous experience with Akka
- Ability to debug complex issues such as finding root causes of high CPU, memory situations, resource contentions, identifying bottlenecks, data query hot spots, etc
#LI-Remote #LI-ST1
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.
Tubi is a division of Fox Corporation, and 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 US-based employees, Tubi offers 12 paid "Tubi Holidays" in addition to the 11 FOX Corporate Company paid holidays
- 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 the birth, adoption, surrogacy or foster placement of a child. 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
Tubi is proud to be an equal opportunity employer and considers qualified applicants without regard to race, color, religion, sex, national origin, ancestry, age, genetic information, sexual orientation, gender identity, marital or family status, veteran status, medical condition, or disability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider employment for qualified applicants with arrest and conviction records. We are an E-Verify company.
