\nProduct Engineer\nHigh level stuff you might be filtering against 🔍\nLocation: Remote (UK timezone +/- 6 hrs generally). In the UK we will hire you as an employee. In other countries you’ll need to be setup as a contractor initially.\nType: Full-time\nSalary: Location dependent. As a reference, our current range in the UK is £75k to £110k. If you will work from another location, you should map this to your equivalent market rate to be competitive. We are open to negotiation as we recognise there are different situations, but these are our general guardrails.\n\n\nWhat I am looking for\n👋 Hi, I’m Martin, VP of Engineering at Zen Educate and I’m looking for engineers who can make an impact on the real world problem of education staffing, and do it through engineering excellence.\n\n\nEvery place has its own understanding of what engineering excellence looks like (sometimes written down, sometimes not). Here’s what it means to me and Zen:\n• Valuing real world outcomes and shared learning over output\n• Product thinking over pure tech - start with the problem, ship quickly and iterate. \n• Team success and sustainability over individual heroics. \n\n\nWe are a small, but mighty team and so every engineer has the opportunity to make an outsized impact and put their stamp on what excellence looks like in practice. What do I mean by “small”? Today we have 4 product teams and 24 engineers including Tech Lead Managers and Principals.\n\n\nWe recognise the world is not static - “what got us here, won’t get us there” - so we look for curiosity, adaptability and proactiveness as fundamental traits. The engineers I see be the most successful are those who focus on solving problems, look to help others and just happen to typically leverage technology to do so.\n\n\nSo whether you’re passionate about building great products, scaling systems, or improving team processes, you’ll thrive at Zen if you care deeply about users, focus on real-world outcomes, pursue continuous learning and strive to make others better 💪\n\n\nWhat we are building and why\nGetting the right teacher into the right school at the right time is a crucial problem to solve, both for education outcomes for children and for the sustainability of an industry that spends billions on this.\n\n\nToday the platform we are building supports internal operations teams on filling roles, educators on finding roles via our mobile app and schools on getting educators in for both short-term and long-term roles. The more we develop the platform (and the ability to self-serve in the marketplace), the more efficient the whole process becomes, which means more money going back to educators and into classrooms (over £30 million since 2017). \n\n\nWe are well established in the UK and growing at a phenomenal rate in the US 🚀\n\n\nWhat we need now is to reach the next level in how we build our platform to support this growth. That’s where you come in 😉\n\n\nWhat the role looks like in practice\nI’ve written a bunch of words above that I hope capture your interest and excitement ✨. But what really matters is what reality looks like and the best people to share that are the existing engineers on the team. So here are a few glimpses from your potential peers of some of what they have done in a week:\n\n\n“I liaised with the Finance team to help re-run a set of invoices that originally failed from our automated invoice service, and I helped implement a feature to convert a long term booking into a job role - to more accurately reflect how teachers work and track job conversions. Then I shared some design feedback for a booking credit system that was initially less well defined.” - Jai\n\n\n“I implemented a compensation system that will cover the additional fees for teachers, which will allow schools to book needed teachers” - Kamil\n\n\n“I was updating the job details view in our React Native app to show more information to teachers about the school and job dates to make the job offers more attractive and useful. I also upgraded our backend Rails app to use latest version of Ruby, Sidekiq, Rack and Puma” - Adrian\n\n\n“I started the week by pushing some small updates to our React Native app, and then finished the week by shipping a feature to improve the experience of schools finding teachers and managing to clean up a bunch of legacy code in the process.” - Chris\n\n\n“I explored the feasibility of using Google Document AI to extract data from documents uploaded by candidates and validate them, improving automation for our onboarding process" - Lucas\n\n\n“I implemented backend and frontend MixPanel events for crucial workflows to better understand how users interact with our product and what we can improve on." - Georgi\n\n\n“I spent some time monitoring Sentry to spot performance trends and debug issues. I also built an automated rota in Coda for our Native release process, before reviewing Product Refinement Docs and contributing to shaping the solutions.” - Ethan\n\n\nWhat you might like or dislike \nEvery place makes tradeoffs based on what they value and where they are in their journey ⚖️. Here’s a list of things you might find useful in figuring out if this is the right role for you. If we end up chatting, feel free to dig deeper into any of them. Note that some of these are recent changes in our approach and may be “work in progress” when you join.\n\n\n💻 How We Work\n• Boring tech for the obvious, experimentation for the rest. Our core is Ruby on Rails, React, React Native, running on Heroku + Cloudflare etc.  But we have also evaluated Amazon Personalise as a candidate for our matching system and spiked out our own AI powered knowledge-base. \n• Process serves performance. We use agile sprints and other structure to support, but our focus is on outcomes not following rules. Greater performance gives greater freedom - think “Master your instrument, master the music, and then forget all that and just play.”\n• Engineers as problem shapers (not ticket takers). You’ll thrive here if you want to shape problems, not just deliver tickets. Our Product Managers and Designers are partners you pull on for leverage rather than task givers who hide the users away.\n• Daily shipping culture. We ship regularly and want to get even better at it. We are investing in this and welcome those who’ll help us start smaller and iterate faster.\n\n\n🌱 Growth & Progression\n• Choose your own career path. We care more about impact and learning than rigid competency grids. This means greater flexibility in what progression looks like, but requires you to build an understanding of what we value from guiding principles and shared real-world examples.\n• Few Titles, infinite Levels. We use Levels instead of Titles to show growth in a Role. You won’t see titles like Associate, Senior, or Staff here. Instead, you can grow continuously by getting better at your current role - e.g. working faster, safer, and more independently. Changing roles is possible too, but depends on business needs, since different roles aim for different business outcomes and typically use different skills.\n• Investment over reward as a mindset. Level changes are tightly coupled to compensation changes. Confidence in a Level change is based on sustainably doing great work at your current level. We think it is fairer to invest in what you do next, rather than reward you doing the next Level first for free!\n\n\n💸 Compensation\n• Market reality. Compensation is based on your competitiveness in your local hiring market (note that’s not just where you live). We don’t believe anyone has found a great solution to global compensation, so we aim instead to be clear and equitable in how we do it.\n• Solid, but not flashy compensation. We pay decently, but we won’t beat out companies with deeper pockets (yet!).\n• Think long term investment. If you are in a place where you need to prioritise immediate financial gain then this probably isn’t the right time to join us.\n\n\n🤝 Team Culture & Collaboration\n• Distributed engineering team. Solid communication skills and async habits are key to be effective. You’ll find strong connection here, but not through engineering getting together in-person. If you like the buzz of working near others you are welcome to work from one of our offices, but there won’t be many engineers there on any given day.\n• We believe in impact and measurable outcomes, alongside shared learning. If your work moves the needle or teaches us something meaningful then that’s a win. If not, then we’ll want to understand why. \n• Balanced, sustainable work. Long hours are not a badge of honour - they are an indication something isn’t working well. We value a sustainable pace and healthy teams.\n• Diversity is good in some ways and lacking in others. You might be the first of something here. That matters and we’ll support appropriately if you are.\n\n\nHow we hire\nHire fast, fix fast.  Hiring today is...not great, with most companies being too cautious and taking too long to make a decision 😦. We move quicker - our ideal is: apply Monday, offer by Friday. Then we invest heavily in the most important part - your onboarding. We ensure you are setup for success, with clear direction, experience of different teams and shipping to production within days.\n\n\nWhilst fast doesn’t mean frivolous, it does slightly increase the risk that you or we made a mistake. So we include regular check-ins during onboarding to make sure expectations match reality. If either side feels something is off then we try to fix it fast. And sometimes that will mean saying “let’s not carry on” with respect.\n\n\nReal talk. We believe in being direct and authentic. We’ll share the good, the messy and the challenges. We recognise we won’t have all the answers, still have much to learn, and that’s all part of the fun of this wild ride 🚀. We expect the same from you - after all we are just a bunch of humans trying to do great work together.\n\n\nMindset, not tools. We hire for how you think and create leverage, not what specific tools you’ve used before. To us, experience is just another tool - it is only valuable through how you leverage it. Curiosity, adaptability, product thinking - those are the durable qualities in a changing world. And we value different opinions, so ensure you share yours - have a point of view, maybe debate a little and we will respect that.\n\n\nAlways open to great people. We are always hiring and happy to chat even if the timing isn’t quite right. That’s why you might see this job post open for a long time. We are not collecting resumes or doing stealth market research, we just believe in the power of serendipity. To make that more transparent - right now we have a clear need for at least 2 more engineers in the team.\n\n\nOkay, so what will the actual process look like? 👀\n• Recruiter quick chat. Our recruiter will check you are human, can communicate effectively and cover some of the basics like compensation, benefits and availability.\n• Technical expertise. We will do a paired session with a twist - we will be the ones sharing our screen and writing the code. So come prepared to ask questions, drive progress with another engineer and dig through an ambiguous past problem in our codebase.\n• Product thinking. Chat to either our CPTO or a Product Manager about how you’ve demonstrated a product mindset in the past. Or if you haven’t had opportunity to do that, tell us why and what you’d do differently with us.  \n• Role chat. This will be with me and I’ll be wanting to understand how you think and approach the role and engineering excellence. I’ll start by asking you the question you include in your application. And I’ll want to dig into your answers so that this becomes more of a conversation and shared exploration than a Q&A session 😃. \n\n\nAfter the recruiter chat, the remaining sessions can happen in any order and as quickly as our schedules can align. You could do them all in a day if you want or spread them out a bit.\n\n\nOnce interviewers have shared their feedback from each session we do an internal debrief - that’s where we discuss what we are excited about you for in the role, any challenges we see and whether we think we can mitigate them at this time. From there we will make a decision and either proceed to offer or tell you that we not offering. \n\n\nWe believe feedback is important, but also know not everyone wants it - so we don’t share it by default. If you’d like feedback after the process, just let us know. Note that we’ll frame the feedback from our perspective of why we did or did not have the confidence rather than as a commentary on you.\n\n\nInterested? Let’s go!\nIf you read all of the above and are excited (maybe even a little nervous) about the opportunity and how we work then I recommend applying now! If you skipped or skimmed the above, feel free to apply anyway but you’re missing a bunch of useful information that could streamline the process for you 😉\n\n\n\n\n\n \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Amazon, React, Ruby, Mobile, Heroku, Engineer and Backend jobs that are similar:\n\n $70,000 — $122,500/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nLondon

The Team\n\nThe AI/ML team is funding and building one of the largest computing systems dedicated to nonprofit life science research in the world. This new effort will provide the scientific community with access to predictive models of healthy and diseased cells, which will lead to groundbreaking new discoveries that could help researchers cure, prevent, or manage all diseases by the end of this century.\n\nAs a hands-on Manager of the AI System Infrastructure and MLOps Engineering team, you will be joining the AI/ML and Data Engineering team in CZI Central Tech, with the responsibility for the stability and scalable operations of our leading edge GPU Cloud Compute Cluster. This supports our AI Researchers in their development and training of state-of-the-art models in artificial intelligence and machine learning to solve important problems in the biomedical sciences aligned with CZI’s mission, contributing to greater understanding of human cell function.\nThe Opportunity\n\nAs the Engineering Manager of the AI Infrastructure and MLOps Engineering team, you will be responsible for a variety of MLOps and AI development projects  that empower our AI Researchers and help to accelerate Biomedical research across the whole of the AI lifecycle. You will guide our AI Systems Infrastructure and MLOps efforts focused on our GPU Cloud Cluster operations, ensuring that our systems are highly utilized, performant, and stable. You will be working in collaboration with other members of our own AI Engineering team as well as the Science Initiative’s AI Research team as they iterate and train their deep learning code, optimizing systems operations and in helping to troubleshoot problems encountered by jobs running on the cluster.\nWhat You'll Do\n\n\n* Help to build out the MLOPs and Systems Infrastructure Engineering team, growing the team to support the large scale capacity systems and AI training efforts we will be undertaking.\n\n* Drive our MLOps processes and System Infrastructure Engineering efforts in ensuring that our GPU Cloud computing systems are highly utilized and stable, and proactively guide our team in implementing the instrumentation and observability tooling integral to our AI Platform.\n\n* Own the on-call efforts for our GPU Cloud computing systems, building out the MLOps and Systems Infrastructure Engineering alerting and monitoring efforts for our leading edge Kubernetes based AI platform, including troubleshooting problems encountered on the GPU platform infrastructure and  with  jobs running on the cluster and computing systems.\n\n* Responsibility for a variety of AI/ML development infrastructure, instrumentation, and telemetry projects that empower our team in supporting our users across the  AI/ML lifecycle, taking a key role in simplifying and optimizing the systems and processes that are integral to our GPU Cloud Cluster operations - in an MLOps meets SRE kind of hybrid operations model.\n\n* Mentoring and managing your team in fulfilling their roles to the best of their abilities, provide skill and career coaching to help the team members keep growing along their own career and life paths, and keep the team engaged in meaningful and interesting projects in service of our north star philanthropic mission\n\n\n\nWhat You'll Bring\n\n\n* Hands-on AI/ML Model Training Platform Operations experience in an environment with challenging data and systems platform challenges\n\n* MLOps experience working with medium to large scale GPU clusters in Kubernetes, HPC environments, or large scale Cloud based ML deployments (Kubernetes Preferred)\n\n* BS, MS, or PhD degree in Computer Science or a related technical discipline or equivalent experience\n\n* 2+ years of experience managing MLOps teams\n\n* 7+ years of relevant coding and systems experience\n\n* 7+ years of relevant coding and systems experience\n\n* 7+ years of systems Architecture and Design experience, with a broad range of experience across Data, AI/ML, Core Infrastructure, and Security Engineering\n\n* Strong understanding of scaling containerized applications  on Kubernetes or Mesos, including solid understanding of AI/ML training with containers using secure AMIs and continuous deployment systems that integrate with Kubernetes or Mesos. (Kubernetes preferred)\n\n* Proficiency with Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, and experience with On-Prem and Colocation Service hosting environments\n\n* Solid coding ability with a systems language such as Rust,C/ C++, C#, Go, Java, or Scala\n\n* Extensive experience with a scripting language such as Python, PHP, or Ruby (Python Preferred)\n\n* Working knowledge of Nvidia CUDA and AI/ML custom libraries. \n\n*  Knowledge of Linux systems optimization and administration\n\n* Understanding of Data Engineering, Data Governance, Data Infrastructure, and AI/ML execution platforms.\n\n* PyTorch, Karas, or Tensorflow  experience a strong nice to have\n\n\n\nCompensation\n\nThe Redwood City, CA base pay range for this role is $214,000 - $321,000. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. Pay ranges outside Redwood City are adjusted based on cost of labor in each respective geographical market. Your recruiter can share more about the specific pay range for your location during the hiring process.\nBenefits for the Whole You \n\nWe’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. \n\n\n* CZI provides a generous 100% match on employee 401(k) contributions to support planning for the future. \n\n* Annual funding for employees that can be used most meaningfully for them and their families, such as housing, student loan repayment, childcare, commuter costs, or other life needs.\n\n* CZI Life of Service Gifts are awarded to employees to “live the mission” and support the causes closest to them.\n\n* Paid time off to volunteer at an organization of your choice. \n\n* Funding for select family-forming benefits. \n\n* Relocation support for employees who need assistance moving to the Bay Area\n\n* And more!\n\n\n\nCommitment to Diversity\n\nWe believe that the strongest teams and best thinking are defined by the diversity of voices at the table. We are committed to fair treatment and equal access to opportunity for all CZI team members and to maintaining a workplace where everyone feels welcomed, respected, supported, and valued. Learn about our diversity, equity, and inclusion efforts. \n\nIf you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.\n\nExplore our work modes, benefits, and interview process at www.chanzuckerberg.com/careers.\n\n#LI-Remote #LI-Hybrid #LI-Onsite \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Amazon, Recruiter, Cloud and Ruby jobs that are similar:\n\n $30,000 — $80,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nRedwood City, California, United States

The Team\n\nThe AI/ML team is funding and building one of the largest computing systems dedicated to nonprofit life science research in the world. This new effort will provide the scientific community with access to predictive models of healthy and diseased cells, which will lead to groundbreaking new discoveries that could help researchers cure, prevent, or manage all diseases by the end of this century.\n\nAs a hands-on Manager of the AI System Infrastructure and MLOps Engineering team, you will be joining the AI/ML and Data Engineering team in CZI Central Tech, with the responsibility for the stability and scalable operations of our leading edge GPU Cloud Compute Cluster. This supports our AI Researchers in their development and training of state-of-the-art models in artificial intelligence and machine learning to solve important problems in the biomedical sciences aligned with CZI’s mission, contributing to greater understanding of human cell function.\nThe Opportunity\n\nAs the Engineering Manager of the AI Infrastructure and MLOps Engineering team, you will be responsible for a variety of MLOps and AI development projects  that empower our AI Researchers and help to accelerate Biomedical research across the whole of the AI lifecycle. You will guide our AI Systems Infrastructure and MLOps efforts focused on our GPU Cloud Cluster operations, ensuring that our systems are highly utilized, performant, and stable. You will be working in collaboration with other members of our own AI Engineering team as well as the Science Initiative’s AI Research team as they iterate and train their deep learning code, optimizing systems operations and in helping to troubleshoot problems encountered by jobs running on the cluster.\nWhat You'll Do\n\n\n* Help to build out the MLOPs and Systems Infrastructure Engineering team, growing the team to support the large scale capacity systems and AI training efforts we will be undertaking.\n\n* Drive our MLOps processes and System Infrastructure Engineering efforts in ensuring that our GPU Cloud computing systems are highly utilized and stable, and proactively guide our team in implementing the instrumentation and observability tooling integral to our AI Platform.\n\n* Own the on-call efforts for our GPU Cloud computing systems, building out the MLOps and Systems Infrastructure Engineering alerting and monitoring efforts for our leading edge Kubernetes based AI platform, including troubleshooting problems encountered on the GPU platform infrastructure and  with  jobs running on the cluster and computing systems.\n\n* Responsibility for a variety of AI/ML development infrastructure, instrumentation, and telemetry projects that empower our team in supporting our users across the  AI/ML lifecycle, taking a key role in simplifying and optimizing the systems and processes that are integral to our GPU Cloud Cluster operations - in an MLOps meets SRE kind of hybrid operations model.\n\n* Mentoring and managing your team in fulfilling their roles to the best of their abilities, provide skill and career coaching to help the team members keep growing along their own career and life paths, and keep the team engaged in meaningful and interesting projects in service of our north star philanthropic mission\n\n\n\nWhat You'll Bring\n\n\n* Hands-on AI/ML Model Training Platform Operations experience in an environment with challenging data and systems platform challenges\n\n* MLOps experience working with medium to large scale GPU clusters in Kubernetes, HPC environments, or large scale Cloud based ML deployments (Kubernetes Preferred)\n\n* BS, MS, or PhD degree in Computer Science or a related technical discipline or equivalent experience\n\n* 2+ years of experience managing MLOps teams\n\n* 7+ years of relevant coding and systems experience\n\n* 7+ years of relevant coding and systems experience\n\n* 7+ years of systems Architecture and Design experience, with a broad range of experience across Data, AI/ML, Core Infrastructure, and Security Engineering\n\n* Strong understanding of scaling containerized applications  on Kubernetes or Mesos, including solid understanding of AI/ML training with containers using secure AMIs and continuous deployment systems that integrate with Kubernetes or Mesos. (Kubernetes preferred)\n\n* Proficiency with Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, and experience with On-Prem and Colocation Service hosting environments\n\n* Solid coding ability with a systems language such as Rust,C/ C++, C#, Go, Java, or Scala\n\n* Extensive experience with a scripting language such as Python, PHP, or Ruby (Python Preferred)\n\n* Working knowledge of Nvidia CUDA and AI/ML custom libraries. \n\n*  Knowledge of Linux systems optimization and administration\n\n* Understanding of Data Engineering, Data Governance, Data Infrastructure, and AI/ML execution platforms.\n\n* PyTorch, Karas, or Tensorflow  experience a strong nice to have\n\n\n\nCompensation\n\nThe Redwood City, CA base pay range for this role is $214,000 - $321,000. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process. Pay ranges outside Redwood City are adjusted based on cost of labor in each respective geographical market. Your recruiter can share more about the specific pay range for your location during the hiring process.\nBenefits for the Whole You \n\nWe’re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible. \n\n\n* CZI provides a generous 100% match on employee 401(k) contributions to support planning for the future. \n\n* Annual funding for employees that can be used most meaningfully for them and their families, such as housing, student loan repayment, childcare, commuter costs, or other life needs.\n\n* CZI Life of Service Gifts are awarded to employees to “live the mission” and support the causes closest to them.\n\n* Paid time off to volunteer at an organization of your choice. \n\n* Funding for select family-forming benefits. \n\n* Relocation support for employees who need assistance moving to the Bay Area\n\n* And more!\n\n\n\nCommitment to Diversity\n\nWe believe that the strongest teams and best thinking are defined by the diversity of voices at the table. We are committed to fair treatment and equal access to opportunity for all CZI team members and to maintaining a workplace where everyone feels welcomed, respected, supported, and valued. Learn about our diversity, equity, and inclusion efforts. \n\nIf you’re interested in a role but your previous experience doesn’t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.\n\nExplore our work modes, benefits, and interview process at www.chanzuckerberg.com/careers.\n\n#LI-Remote #LI-Hybrid #LI-Onsite \n\n#Salary and compensation\n No salary data published by company so we estimated salary based on similar jobs related to Design, Amazon, Recruiter, Cloud and Ruby jobs that are similar:\n\n $30,000 — $80,000/year\n
\n\n#Benefits\n 💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
\n\n#Location\nRedwood City, California, United States