Software Engineer, ML Infra, Distributed Systems – Staff, Principal
Jobtailor
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.
Requirements
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.
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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.
Requirements
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.
#J-18808-Ljbffr
Reference: WJ-3875_12811585