Site Reliability Engineer - Machine Learning
Who We Are
Twitter is looking for a Site Reliability Engineer to join our Machine Learning consumer product teams. SREs will be dedicated to scaling our infrastructure, improving developer productivity, automation and tooling that power impactful features on Twitter, like the Timelines, Notifications, Search, Trends, and so much more.
You will be working with machine-learning engineers or applied data scientists who work on algorithmic and deep infrastructure issues, massive scale graph mining, recommendation systems, information retrieval systems, natural language processing, etc.
What You’ll Do
- You will help us identify and develop solutions to improve scalability, performance and simplify our platform and processes
- Advocate for reliability and develop standards across services and teams
- You will drive standardization efforts across multiple disciplines, systems, software, and teams
- Maintain services once they are live by measuring and monitoring availability, latency and overall system health
- Support critical offline big data scalding and analytic jobs
Who You Are
- You have a solid understanding of systems and application design, including the operational trade-offs of various designs
- You have a systematic problem-solving approach
- You have strong communication skills and a sense of ownership and drive
- Be adaptable and able to focus while working with large, complex, and multi-team owned services
- Can take initiative on tasks and work well in a remote team environment
- B.S. in computer science or similar field or equivalent experience
- Minimum 2+ years of handling services in a large scale distributed environment
- Practical, proven knowledge of shell scripting and at least one higher-level language (eg. Python, Ruby, Golang)
- Demonstrable knowledge of TCP/IP and HTTP
- Travel to our SF office at least a couple of times a week
We are committed to an inclusive and diverse Twitter. Twitter is an equal opportunity employer. We do not discriminate based on race, color, ethnicity, ancestry, national origin, religion, sex, gender, gender identity, gender expression, sexual orientation, age, disability, veteran status, genetic information, marital status or any legally protected status.
San Francisco applicants: Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Engineering Hiring Process
Once your application is received, a recruiter will reach out pending your qualifications are a match for the role.
If your background is a match, you may have 1-2 technical phone interviews or be given the chance to provide a work sample depending on the role.
If the phone interviews go well or your work sample is strong, the final step includes interviews with 5-6 people held onsite in our office.
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