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Hiring
40 posts about Hiring. Every summary links to the original.
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Who We Hire at Supabase
Supabase describes the hiring traits and operating model it believes support its growth, arguing that people matter more than methodology. It looks for extreme asynchronous effectiveness, egoless execution, continuous incremental improvement, a bias toward immediate action, ambitious problem-solving, and a founder mindset; seniority does not exempt anyone from independent-contributor work, self-management, or maintenance. The 60-person team spans 25 countries, uses meetings as a last resort, and gives autonomous product teams access to shared metrics, user feedback, and equity through an ESOP. Teams are organised around products such as Postgres, Auth, Storage, Realtime, and Functions, while cross-cutting groups consult rather than merely receive delegated tasks. Three-month product cycles set ambitious goals, and Kaizen Weeks focused on QA, documentation, and performance help address technical debt and incorporate improvements into ongoing workflows.
Shopify’s Technical Interview Process: What to Expect and How to Prepare
Shopify’s guide outlines the interview process for individual-contributor technical roles, while noting that stages can vary by role and team and that leadership hiring may add team-specific interviews. Candidates may have a one-hour recruiter “Life Story” conversation, a 40-minute CoderPad coding exercise, a 75–90-minute remote pair-programming session, and a 60-minute Technical Deep Dive focused on previous projects. The coding exercise assesses algorithmic thinking and problem solving, while pairing emphasizes communication, implementation, edge cases, scalability, limitations, and testability. The deep dive asks candidates to discuss impact, architecture, technical decisions, trade-offs, failures, successes, lessons learned, teamwork, and mentorship; the guide also recommends clarifying questions, running code early, using permitted references, and choosing projects they know well.
We Raised $100 Million for Open & Collaborative Machine Learning 🚀
Hugging Face announced a 100 million dollar Series C funding round led by Lux Capital, alongside participants including Sequoia, Coatue, and several angel investors. The platform hosts over 100,000 pre-trained models and 10,000 datasets spanning natural language processing, computer vision, speech, and other scientific domains for more than 10,000 customer organizations. The company plans to use the capital to expand research, open-source initiatives, tooling, and efforts focused on mitigating machine learning limitations like biases, privacy risks, and energy consumption. In addition, the organization is directing the BigScience research workshop with over 1,000 participants to train a massive open-source multilingual language model. Following organizational growth from 30 to more than 120 employees in twelve months, the remote-friendly company is actively hiring across all positions and seniority levels.
Should I Open Source my Company?
Software founders often hesitate to make their companies open source due to concerns regarding code scrutiny, security exploits, and intellectual property theft. Supabase operated as an open-source business from its inception, finding that community scrutiny actually accelerates code refactoring and surfaces security vulnerabilities early through public reporting channels. In addition, rapid execution and developer experience provide stronger competitive defenses against larger competitors than proprietary code obfuscation or software patents. Open repos also transformed the company's hiring strategy by replacing traditional take-home tests and LeetCode interviews with evaluation of real-world pull requests and asynchronous discussions. Finally, external contributors expand product capability by independently developing niche integrations and platform adapters that core startup teams lack the bandwidth to build.
Machine Learning Experts - Margaret Mitchell
Machine learning models often internalize harmful dataset skews and fail to evaluate real-world contexts accurately. During work on vision-to-language generation, visual recognition systems learned to misinterpret destructive disasters as positive scenes because training images predominantly featured sunsets and fireworks. Addressing these structural flaws requires moving beyond benchmark optimization toward critical data analysis, dataset genealogies, and standardized ethical AI protocols. ML organizations must establish shared vocabularies for power differentials and dismantle competitive cultural norms that marginalize underrepresented contributors. Furthermore, lowering technical barriers—such as enabling non-engineers to inspect data without SQL—allows diverse stakeholders to evaluate models and prevent widening societal power divides.
Announcing the 🤗 AI Research Residency Program
Hugging Face launched a nine-month Research Residency Program designed to train participants into impactful machine learning researchers. Residents collaborate directly with researchers from the Science Team to formulate research questions, develop novel machine learning techniques, and openly publish their findings. The initiative specifically encourages proposals from marginalized groups—including women, LGBTQ+ individuals, people of color, and working-class communities—to address disparities exacerbated by artificial intelligence progress. Applicants must demonstrate mathematical and programming abilities through coursework, open-source projects, and end-to-end proposals targeting positive societal impact. The full-time role is fully remote, provides benefits including medical coverage depending on location, and excludes concurrent student enrollment or employment.
How to Get an Engineering Internship at Shopify: A Complete Guide
Shopify’s guide describes its engineering internship program as a way for students, recent graduates, career switchers, and bootcamp graduates to gain hands-on experience through real projects and practical feedback. Internships last three to eight months and span front-end, back-end, infrastructure, data, and mobile development, with three application cycles each year. Applicants submit an online application, complete an Intern Challenge or specialization-specific skills assessment, and progress through a two-phase interview involving a Life Story conversation and a technical solution. The guide identifies collaboration, lifelong learning, curiosity, GitHub experience, remote-work experience, communication, and accountability as important skills, while recommending practice challenges, project portfolios, and company research; 98% of respondents in Shopify’s latest intern satisfaction survey said they would recommend the program.
Lessons from my internship at Ramp
The author reflects on a three-month software engineering internship at Ramp from March to June, describing lessons about execution, company choice, and location. Ramp’s charge card appeared to be a commodity, but the author credits its bias for shipping quickly, technical and product strength, differentiated technology, and favorable capital secured through finance expertise with turning it into a distinctive product. Compared with more formal, lower-stakes internships, Ramp offered flexibility, mentorship, and exposure to a fast-growing organization, although its pace and limited documentation could be challenging. The experience also shaped the author’s view that working on large problems at such a company can magnify impact, while New York provided experiences and a tech community distinct from San Francisco’s.
Making big bets in business
The post argues that startups should pursue asymmetric outcomes: bets with potentially large upside and limited, manageable downside, rather than optimizing for average advice or minimizing every risk. Drawing on the founders’ experience building Paribus and Ramp, it applies this principle to choosing a problem space, hiring, vendors, product development, and fundraising. An outsized seed round enabled Ramp to pursue financial services despite high barriers to entry, while early hiring favored exceptional, fast-growing people over candidates who matched every competency checklist. It also recommends testing scrappy vendors, listening to customer problems rather than proposed solutions, and selecting reputable investors with clean terms. Ramp’s counterexample is credit risk: because revenue is about 1% of lending, a mistake can cost roughly 100 times its reward, so threatening risks should be isolated from bolder bets.
Fly.io Is Hiring Full-Stack Developers
Fly.io is seeking early-to-mid-level full-stack developers to work on customer-facing parts of its global application-hosting product. The role sits in a CLI-first organization whose UX stack combines Rails, GraphQL, and Go, with more Elixir and Phoenix planned, while the broader platform uses Rust and Go. Candidates are not expected to be Rails or Elixir experts; the stated bar is the ability to learn unfamiliar code and produce work that holds up, including deploying an application end to end and building browser UI components. Hiring centers on untimed work-sample challenges based on the team’s actual work rather than resume screening, interview gauntlets, or gotchas. The remote full-time role offers US healthcare, flexible vacation, hardware and phone allowances, and $120k–$140k plus equity.
Supabase Partners With Strive School To Help Teach Open Source
Supabase has partnered with fellow Y Combinator Summer 20 alumni Strive School to teach upcoming software engineers open-source development practices. Strive School operates an eight-month training program in Europe covering full-stack web and artificial intelligence engineering, with students paying tuition only after securing employment. Through this collaboration, Supabase aims to improve relational database instruction using Postgres while producing exclusive educational content for the program. In addition to creating learning materials, Supabase is hiring a Strive School graduate as an intern to integrate new engineering talent into its team. Supabase is also introducing a Student Developer Pack offering two years of free platform credits, Slack community access, founder office hours, and merchandise.
Supabase Alpha June 2020
Four months into development, Supabase released its June 2020 alpha update focused on simplifying PostgreSQL management and eliminating regional performance bottlenecks. The release introduces a spreadsheet-like interface for drilling down into relational tables alongside automated detection and editing support for JSON and JSONB columns. To address latency issues previously caused by hosting all projects exclusively in Singapore, the platform now allows developers to select specific database regions. In line with its zero lock-in principle, Supabase exposed daily backups on the dashboard and enhanced the SQL editor with improved syntax highlighting. The team also expanded by hiring PostgREST maintainer Steve Chavez while continuing efforts toward future multi-region replication and WAL-G backup integration.
7 Fun Facts about Grab’s Driver-Partners in Singapore
Grab analyzed ride-hailing metrics from driver-partners operating in Singapore to identify platform usage trends and driving patterns. Findings indicate that drivers have a 1 in 400 chance of encountering a repeat passenger among the 5.4 million population, with Tampines recording the most pickups and Orchard and Marina Bay serving as top destinations in 2018. Driver behavior data shows that partners with over two years of platform experience routinely start shifts an hour earlier and leverage auto-accept features to minimize idle waiting time. Furthermore, drivers are twice as likely to receive back-to-back ride allocations during evening peak hours, resulting in roughly 50% higher hourly earnings. The dataset also highlights customer satisfaction metrics, showing that shared GrabShare rides achieved an average rating of 4.8 stars.
How Shopify Scales Up Its Development Teams
The article argues that scaling development is primarily about creating more effective teams, not simply increasing headcount. It first recommends checking whether an existing team prioritizes impactful work, minimizes supporting activity, and can ship code quickly while finding bugs; otherwise hiring may be premature. Shopify organizes product work into problem spaces and teams of five to nine, uses a multi-step process combining technical exercises with cultural assessment, and aims for at least as many onboarded members as onboarding members. New teams receive a baseline for work practices and technology, while transparent technical design, shared tooling with dashboards and embedded quality and testing standards, optional pairing, and frequent retrospectives support consistency and learning. The conclusion is that these practices, rather than hiring alone, enable development teams to scale more effectively.
Lessons from Leading a Remote Engineering Team
Managing remote engineering teams can expand hiring beyond office locations, support a more diverse workforce, retain employees through relocations, and enable distributed coverage such as 24/7 support. The guidance describes building such teams around relationships, trust, and communication, with “Default to open internally” and “Charge your trust battery” as supporting cultural values. It recommends asynchronous documentation and discussion in email, GitHub issues, Google Docs, and project systems, supplemented by a fixed weekly synchronous meeting and shared core hours. Managers should also support healthy home workspaces, maintain regular one-on-ones and timely contact, arrange selective in-person sessions, and actively champion remote employees’ visibility, recognition, and career progression. The approach requires deliberate effort but can provide hiring, composition, retention, and strategic benefits.
The Art of Hiring Good Engineers
Building and scaling engineering teams requires adapting recruitment strategies across different organizational sizes, from initial hires to hundreds of engineers. Teams often begin with small groups of battle-tested engineers before designing formal hiring pipelines. The recruitment approach outlines four key steps: sourcing top-tier talent from platforms like GitHub and LinkedIn, assessing technical fit through tailored screens or assignments, evaluating cross-functional and culture fit via group interviews, and optimizing the process. This optimization includes routing candidates strategically to strict bar-raiser interviewers to prevent burnout and expedite decisions.
So You Need to Hire Good Engineers
Hiring strategies in fast-growing technology startups dictate the quality and scalability of expanding engineering teams. Insights gathered from conversations with over one hundred engineering leaders identify crucial evaluation criteria across technical competence, cultural alignment, and problem-solving capability. Candidates rarely present a perfect technical fit, requiring hiring managers to weigh passion, willingness to learn, and risk appetite against baseline technical requirements. Rather than focusing solely on static factual questions, interviewers gain deeper insights by probing the rationale behind candidates' architectural and implementation choices. High-caliber engineers ultimately elevate team capability by simplifying complex challenges, writing cleaner code, and learning quickly.
How Grab Hires Engineers in Singapore
Grab maintains a selective engineering recruitment process in Singapore, with only three to five percent of candidates ultimately receiving an offer. The evaluation pipeline typically spans three to four weeks and includes an initial HR phone screen, an online coding round, and consecutive technical interviews. Recruiters assess candidate capability via public GitHub projects, presentations, and technical blogs rather than traditional CV qualifications alone. The company prioritizes experience in low-latency distributed systems and microservices design alongside strong cultural alignment with peer collaboration.
Battling with Tech Giants for the World's Best Talent
Grab maintains research and development centres across Singapore, Seattle, and Beijing to develop mobility and transaction platforms for Southeast Asia. Engineer Brandon Gao turned down an offer from a major Seattle-based technology corporation to remain at the company due to rapid growth and high engineering impact. During backend infrastructure changes starting in May 2015, Grab transitioned core services from Node.js and Ruby to Golang. A weekend Golang prototype created by Gao evolved into the primary data service linking backend servers to 580,000 drivers across the region. Additionally, his initial work on the User Trust team established a machine-learning risk and fraud detection system supporting large-scale mobile transaction volumes.
Grab Vietnam Careers Week
Grab announced its first Grab Vietnam Careers Week, held in Ho Chi Minh City from 22 to 26 October 2016, aimed at hiring engineers to improve regional transportation and reduce congestion. At the time, Grab operated on 23 million mobile devices supported by 460,000 drivers across Southeast Asia. The announcement features an interview with Singapore-based iOS engineer Hai Pham and Android engineer Son Nguyen discussing team culture, regular hackathons termed "Grabathons", and relocation to Singapore. Technical candidates undergo a Codility test and are evaluated on clean mobile architecture, testing, and performance maintenance. The engineers also offer advice on apartment hunting through online community forums and adapting to life in Singapore.
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