– Faisal Z Siddiqi. [This post first appeared on LinkedIn]
A Personal glimpse into my first 100 days at Netflix
Netflix had always been a company I admired. For me, it was the quintessential disruptor – continually changing the entertainment landscape in America. Its video apps were synonymous with strong user focus, its Culture deck was a one-of-a-kind manifesto making the rounds in Silicon Valley, and its TechBlog was a resource I had enjoyed reading for years.
But as I evaluated the opportunity to lead an engineering team at Netflix, the pragmatist (read, skeptic) in me wondered how things would really be behind the scenes. How real was the culture of freedom and responsibility? Could a 17+ year old “big” company operate nimbly? Given it was no longer an upstart with an open canvas, would there still be learning for me? How much growth potential did the company itself have? After some interesting probing conversations with the team at Netflix, I decided to take the plunge.
This is my personal perspective after 100 days at Netflix.
The week I joined was the week of the 360 reviews, where each employee provides feedback to whoever they have materially interacted with over the year. It’s a simple no-frills write-up on what they should continue and what they should change. This includes reviews for peers as well as folks up and down the management chain. What stood out, however, was the complete honesty expressed in the feedback, and the prompt follow up for anything that appeared to be a surprise. Employees are encouraged to give continuous and direct feedback throughout the year, so there are no surprises come 360 review time, but the intent of the 360’s is to highlight the most meaningful feedback you have for your co-workers. And there is a lot of continuous direct feedback. It’s not unusual for an engineer to go up to his or her VP and tell them what they should be doing better. I found it to be a great course-correcting device as I started getting feedback from my team, both directly as well as indirectly through my manager.
This type of feedback system can only flourish when you have a foundational culture of “Freedom & Responsibility”. The culture is something you will hear about a lot in the interview process and throughout your time at Netflix. The focus on freedom and responsibility is the single most influential tenet of Netflix’s culture and you can read more about it here. In essence, employees have freedom over vast areas of engagement, as long as they take the responsibility to own the process and use good judgment to make decisions that are in Netflix’s interest. This informs the hiring decisions as the company tends to value culture-fit very highly in a potential candidate. As an example, if you want to build a new tool using TheLatestAndGreatestProgrammingLanguage, you don’t need any permissions – you just go ahead and do it, but it’s your responsibility to think about the maintainability, support, and evolution of the tool in a way that is scalable. The “you don’t need any permissions” policy applies to a large number of things. And for the littlest of things, it’s surprisingly liberating, and efficiency-boosting.
Within my first thirty days, I experienced another unique Netflixism. Nobody told me this in the interview process, but every quarter there is a company meeting where newbies perform on stage in front of the whole company. Not the kind of creativity I thought was expected of me. I don’t know about you, but prancing on stage as a no-nonsense Agent of S.H.I.E.L.D in front of all your co-workers, isn’t exactly my idea of getting introduced to my colleagues. In true Netflix Original fashion, though, I had a blast.
I manage the Personalization Infrastructure team at Netflix. The charter for my team is to accelerate the pace of video discovery innovation for Netflix. We build systems and frameworks for personalized video recommendations. Netflix is very data-driven and almost all facets of the user experience are A/B tested. You are always hearing about which cell is green or flat, meaning which sub-feature rolled out to a small percentage of Netflix customer base seems to show a positive statistical significance, or the lack thereof. We have a lot of applied machine-learning (ML) researchers who come up with the latest ML algorithms, features and models. It’s my team’s job to increase their efficiency, providing them with a platform that allows them to iterate fast. This includes putting together a best-of-breed collection of open source technologies to build a service that, say, allows the researchers to “turn back time” by using snapshots of various micro-services. Or it may mean building an orchestration engine for ML pipelines from the ground up. Netflix has a rich history of Open sourcing and engineers are encouraged to think about open-sourcing opportunities as they go about doing their job. My team also builds and innovates on caching infrastructure for internal micro-services, built on top of memcached and optimized for public cloud usage across global regions. This service is one of the most heavily used pieces of software across engineering teams at Netflix and has been my portal into learning about the scale we deal with on a daily basis. Throughputs on the order of 300,000 requests per second on one replicated production cluster with low milliseconds of latency are not unusual. This software is already open-sourced, but we are working on a major cleanup and will be doing a long overdue round of updates to the open-sourced version in the coming months.
As most teams do here, the talented engineers on my team are honest, nimble and have little patience for “process overhead”. It took a while to get used to being told “this is not the Netflix way”. What I have learned in my short time here is that a leader can be much more effective with a highly skilled team if they set appropriate context, facilitate the right tools, connect the dots as new opportunities arise, and then get out of the way. In the time I have been here my team has hosted a Netflix Meetup engaging with the Apache Spark community, talked about our experience building machine learning pipelines at the Spark Summit 2015 and invited several guest speakers, often budding entrepreneurs, to talk about their solution and to exchange ideas with them.
The team works on distributed systems at scale using a host of emerging technologies and is a heavy user of Scala and Java in the cloud. You get to own your service/tool from conception to requirements, design, development, testing, deploying, and being on call for it. We have seen that this responsibility, combined with the motivation to not be paged in the middle of the night, often results in better self-healing software. Netflix has a great toolchain for monitoring and deploying software, and the Engineering Bootcamp provides a quick ramp-up for folks on the Netflix ecosystem. The team is growing and we have big plans for the upcoming months.
As I have been interviewing candidates, once in a while someone brings up Netflix’s reviews on Glassdoor. Frankly, I was reading them myself when I was contemplating employment here. Now that I have had some time to see things on the inside for myself, Quora’s non-anonymous responses seem to be far more balanced to me. As an example, there seems to be a perception that Netflix’s unlimited vacation policy is really an underhanded way to extract the most out of employees as there are no set holidays. Nothing could be further from the truth. It’s not uncommon to have employees take multi-week vacations, for more than a month at times. It’s amazing how effective well-rested employees can be.
It has not all been rosy, of course. I’ve had to grapple with reconciliation of at least partially overlapping tools built across teams, have tough conversations to give honest feedback to my team and management, and explain how an otherwise stable system could result in providing a certain employee with a not-so-personalized video recommendation (let’s just say not everyone enjoys Barbie videos!). That is very much a part of the learning experience I was seeking though, and ultimately, it’s how much you get out of your comfort zone that determines how much you may grow. And it’s best done with amazingly talented, humble, and responsible colleagues.
As I look forward to my journey at Netflix, I often think about the impact the company has had around me. My 5 year old daughter knows that Netflix is “Abba’s office”, but yesterday she surprised me with a “Oh, it’s also a button on my iPad… you press it to play kids shows”. I was promptly informed of her favorites, WildKratts, Sophia the First, Clifford and SuperWhy. She gave me an unsolicited demo, clicking through the Kids profile onto WildKratts in the Character Bar – a demo which would give many a product managers a run for their money. For someone who spent the last 15 years working in the “hard-to-explain-to-family-what-I-do” enterprise space, it’s a welcome change to work for a brand my pre-kindergartner can love and enjoy. It also bodes well for a service that wants to win more and more entertainment “moments of truth” for an increasingly global demographic.
Earlier this year, Reed talked about the intention to launch in 200 countries by end of 2016. Today, Netflix is bustling with energy around the push to go global. We have folks working on dubs/subs localization, UI treatments, localized marketing, global cloud infrastructure, and globalization of personalization algorithms, among others.
Which brings me to the banner image of this post. No, its not an upcoming Netflix Original. It’s the image from a T-Shirt I designed for Netflix engineers playing in a corporate cricket league. I chose it for this post because now I believe that like the trailblazing ball in this image, Netflix is going places. Literally.