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Hey, I'm Tadas . I'm hiring a Senior Product Data Engineer for Data Insights, the team that builds Modash's data products. Modash helps brands find, understand, and work with creators on Instagram, TikTok, and YouTube. More than 2,700 companies, including Stanley 1913, Sennheiser, and NordVPN, use us to run and grow their creator partnerships. Data Insights turns raw social media data into the datapoints customers buy: which brands a creator has worked with, how to contact them, where they're based, and which other creators are like them. Most of the work is taking messy public data across 200M+ profiles and making it accurate enough that a brand will act on it. In this role you'll own datapoints end to end, from the raw signal to what the customer sees, and you'll be judged on their quality. Why we're hiring At Modash, the data is the product customers pay for. Brands use our collaboration, contact, and location data to decide which creators to work with, and our largest customers take it in regular bulk deliveries through our API. We need a senior engineer who can take one of these datapoints from a rough idea to a production pipeline and keep improving it after launch. Right now that means building our own creator-location data, using LLMs to find and validate creator contact emails, and matching sponsored posts to the right brand and its parent company. You'll join a team of four data engineers who work closely with four backend engineers. You'll make important technical decisions yourself, with strong teammates to back you up, and customers will see what you build. For a feel of how we build software, read our Engineering Blog . What you'll own 1. Build the datapoints customers pay for. You'll turn raw posts, bios, and profile data into signals: brand collaborations, contact details, creator location, related creators, and links between one creator's accounts on different platforms. 2. Make data quality measurable. Every datapoint we ship has automated quality checks. You'll decide what good looks like for your datapoint, measure it per platform against real coverage numbers, and catch regressions before customers do. 3. Take projects from idea to production. You'll shape the problem, scope the work, design the architecture, write the code, ship it, and learn from how it performs. We expect senior engineers to own the outcome, even when the problem arrives half-defined. 4. Use LLMs where they pay off. We run LLM enrichment at large scale. You'll decide where an LLM beats a rule or a simpler model, and work out what it costs across 200M+ profiles before it ships. What the day-to-day looks like Most weeks you're on one project for days at a time, with some of your time going to pipeline issues and code review. A typical week might look like this: • Monday. You spot-check your datapoint's output and find a quality problem. You write a short plan for fixing it and get feedback from another data engineer before you start. • Tuesday. You build the change in PySpark and test it. It's too slow on the full dataset, so you profile the job and fix it. • Wednesday. A pipeline failed overnight. You find the cause, ship a fix, and rerun it. In the afternoon you review a teammate's PR, then get back to your project. • Thursday. You compare results before and after the change on each platform. One number moves more than expected, and you dig in until you can explain it. • Friday. You merge, watch the first production run, and check the quality reports. You answer a question from a backend engineer about the data, then plan next week. Every meeting needs a reason, and we protect time for focused work. You'll have a short standup, pair with people when it helps, and get long stretches to plan, build, and ship. Requirements What you've done before • Built data systems at meaningful scale. You have solid experience as a data engineer and have worked with large, complex datasets in production. • Worked deeply with Spark. PySpark, Scala, or Databricks all count. We use PySpark, but strong Spark fundamentals matter more than the exact flavour. Here is the blog post that helps explain the kind of work we do. • Turned messy data into signals people rely on. Entity matching, classification, deduplication, or enrichment: you've built reliable output from data that started out incomplete, inconsistent, or wrong. • Treated data quality as part of the job. You've defined quality checks, tracked coverage and accuracy, and handled a quality drop like a bug. • Owned full features. You've taken a feature through planning, scoping, architecture, implementation, release, and iteration. • Written production Python and SQL. You care about code quality, system design, and maintainability. • Worked with orchestration and cloud infrastructure. Experience with Airflow or AWS Step Functions, and with services such as EMR, Glue, Athena, DynamoDB, S3, Kinesis, Lambda, or ECS, will help you get moving quickly. • …

Hi, I'm Willi , and I lead Product at Modash. I'm looking for a Senior Product Designer/Product Manager to own the payments experience in our Payments/Creator team. Background & reason for hiring Modash helps brands scale creator partnerships on Instagram, TikTok and YouTube. Brands pay creators in lots of different ways: free products, one-time payments and affiliate commissions. Today those are separate flows rather than one coherent experience. This role is about building one payment experience that handles all of them, on both sides: • Brand side - setting up the deal and paying for it • Creator side - getting paid You own the entire workflow end to end. The role combines design and product management in one person: you decide what to build and why, and then you design how it works. This is what you'll own: The payments experience Free products, one-time payments and affiliate commissions, for brands and creators alike, from setting up the deal to the creator getting paid. You work on prototypes and concepts for future iterations, design them, collect feedback and get the requirements ready for engineering. Running development cycles • Prepping user stories and explaining them to the engineers • Doing the QA once the work is ready • Giving and receiving feedback in retros • Deciding when it's good enough to get into customers' hands - it's your product The customer voice and the story • Talking with customers about their pains and needs around paying creators, gifting products and running affiliate programs • Keeping everyone in the company up to date on your roadmap, new releases and plans for the next sprints • Working closely with product marketing so your product stands out and customers understand what's new • Tracking your impact using customer feedback and north star metrics Your first months in Modash will bring • Onboarding with the product and Creator teams on how brands and creators use Modash today • Customer calls with brands and creators, plus time in Fullstory and Amplitude to see where the payment flows break down • Joining sprint planning with the engineering team and getting to know the backlog Team structure You'll report to me (Head of Product) and work closely with a dedicated engineering team lead Besnik . You'll also join a group of talented designer/PMs Renata , Maksym & Heidi who own other parts of our B2B SaaS product, and you'll work with them on product ideas, the shared design system and synced roadmaps. Requirements Required skills and experience • Experience as both a product designer & product manager or in a hybrid PM/design role, ideally at a B2B SaaS company • You've written great user stories and communicated your designs clearly to developers • You've prioritized work with a bigger goal in mind and built a roadmap yourself. You can explain why some things came first and others didn't make the cut. • You've worked with a design system to keep the experience coherent • Extreme attention to detail. You notice the wrong spacing, the unclear label and the missing edge case, and you don't ship sloppy work. • Get-it-done attitude. We all run into roadblocks every day. We're looking for someone who finds solutions, motivates themselves and keeps getting things done. • You're used to, and actually enjoy, a fast pace and constant change in a growing company • You aspire to be great. We're not shooting for mediocrity here. • Interest in the creator economy. Our mission is to help creators get paid. You don't need to live and breathe the creator world, but we'd like your values to align with ours. • You're fluent in English. Our team is spread across many countries, and we work together in English every day. Nice to haves: • UX work on affiliate, marketplace or payments products • Strong instincts in research or analytics (you don't need to be an expert in both) • Experience with our tools: Figma, Linear, Notion, Amplitude and Fullstory If you meet most but not all of these, don't let that stop you from applying. We're not looking for a finished product, and we'd be happy to grow with you. Benefits What we're offering • Fully remote working in Europe As long as you have a reliable internet connection, work wherever is best for you. At home, in a café, on a beach. Whatever works. • Compensation. Your compensation is made up of salary and stock options. As we're growing fast, the stock option package is especially significant. Annual salary range is 65,000€ - 85,000€ for this role. We hire across Europe, so the exact number depends on your location, employment type, skills, and experience. • Flexible working hours ⏱ We trust you to do your job without anyone looking over your shoulder. Do your best work whenever it suits you. • Unlimited paid vacation If you're happy and well rested, you'll do better work. Take the time you need to enjoy a balanced life. • Personal development When you grow, we benefit. If there's a …

Hey, I'm Andrei . I’m hiring a Senior Backend Enginee r to join the Data Core team at Modash. Modash helps brands find, understand, and work with creators across Instagram, TikTok, and YouTube. More than 2,700 companies (including Stanley 1913, Sennheiser, and NordVPN) use us to manage and scale their creator partnerships. Every one of those products depends on fresh, reliable creator data. Data Core owns the systems that collect and maintain profiles for 400M+ creators across social platforms, process billions of data points, and keep the rest of Modash supplied with the raw material it needs. That’s where you come in. Why we're hiring Data Core isn't an internal support team. It owns the collection infrastructure that the entire Modash product (and every downstream data team) depends on. Collecting social data at this scale is a hard distributed-systems problem. APIs change without warning. Providers become unreliable. Platforms rate-limit requests. Data grows stale. A tiny inefficiency becomes expensive when repeated hundreds of millions of times. We need a senior engineer who can design resilient services, make thoughtful tradeoffs between coverage, freshness, reliability, and cost, and take production-critical systems from a rough idea to dependable operation. You’ll join the specialised Data Core team and work closely with Data Search, Data Insights, product teams, and company leadership. You’ll have real ownership, but you won’t work in isolation. If you want a feel for how we think about building software, check our Engineering Blog . What you'll actually own 1. Keep creator data flowing at massive scale. You’ll build and evolve the systems that collect and maintain 400M+ creator profiles across Instagram, TikTok, and YouTube, keeping billions of data points fresh enough for search, analytics, APIs, and customer-facing products. 2. Make collection resilient when the outside world isn't. You’ll design services that handle third-party API instability, rate limits, provider outages, platform changes, and partial failures without turning every disruption into a customer incident. 3. Improve the economics of collection. At this scale, every request, proxy call, retry, storage decision, and compute cycle matters. You’ll improve coverage and freshness while keeping the system financially sustainable. 4. Own production, not just the code. You’ll shape the problem, design the architecture, write and review the code, ship it, observe it, and improve it. You’ll build the monitoring and operational safeguards that catch gaps and regressions before customers do. What the day-to-day looks like Here’s what a typical week might include: • Monday. A social platform has changed its behaviour overnight. Collection success has dropped, but only for part of the traffic. You trace the failure pattern, protect downstream freshness, and design a resilient fix rather than a brittle patch. • Tuesday. Deep-focus time. You redesign part of the subscription system that decides which creators to collect, when, and how often, balancing customer value against request and compute cost. • Wednesday. You pair with a Data Search engineer on an indexing dependency. Together, you agree on a cleaner contract that improves freshness without coupling the two teams’ systems. • Thursday. You review a new request-routing approach across proxy providers. You model throughput, failure modes, and unit economics before shipping a small production experiment. • Friday. An observability review reveals a slow coverage regression that existing alerts missed. You improve the data-quality checks so the team catches the next one before it reaches customers. We keep meetings purposeful and protect time for deep work. You’ll have a short standup, close collaboration when it helps, and plenty of space to design, build, harden, and operate systems. Requirements What you've done before • Built large-scale backend or data systems. You have solid experience with high-volume services where reliability, throughput, latency, and cost all matter. • Shipped systems from concept to production. You’ve owned scoping, architecture, implementation, release, operation, and iteration, not just one layer of the solution. • Designed distributed systems. You can reason clearly about partial failure, retries, idempotency, backpressure, scaling, and operational tradeoffs. • Built resilient integrations. You’ve worked with third-party APIs or other external dependencies that are rate-limited, unstable, or liable to change. • Worked with proxy management or request routing. You understand the practical challenges of routing high-volume traffic and navigating anti-bot systems responsibly at scale. • Taken operational ownership. You care about observability, alerting, runbooks, and what happens after deployment, not just whether the code merged. • Worked autonomously on ambiguous problems. You know how to gather requirements, ask useful …

Hey, I'm Adrian . I’m hiring a Senior Software Engineer to join the Data Search team at Modash. Modash helps brands find, understand, and work with creators across Instagram, TikTok, and YouTube. More than 2,700 companies (including Stanley 1913, Sennheiser, and NordVPN) use us to manage and scale their creator partnerships. Every one of those products depends on fresh, reliable creator data. Data Core owns the systems that collect and maintain profiles for 400M+ creators across social platforms, process billions of data points, and keep the rest of Modash supplied with the raw material it needs. That’s where you come in. Why we're hiring Search at Modash isn't an internal platform or a support function. It is one of the core products customers use to discover creators. The scale is large, the data is messy, and the search intent is often complex. A customer might be looking for creators in a specific niche, people whose content conveys a certain visual style, or accounts that resemble a group they already know. Solving that well requires more than adding another filter or calling an LLM API. We need a senior engineer who can work across the full retrieval system, from data and indexing pipelines to embeddings, ranking, relevance, and low-latency serving, and take ambiguous product problems all the way to production. You’ll join the specialised Data Search team and work closely with Data Core, Data Insights, product teams, customers, and company leadership. You’ll have real autonomy, but you won’t work in isolation. If you want a feel for how we think about building software, check our Engineering Blog . What you'll actually own 1. Make creator search meaningfully better. You’ll improve how customers discover creators across 400M+ profiles and billions of media files. That includes retrieval, filtering, ranking, relevance, speed, and the product decisions that connect them. 2. Turn multimodal data into searchable intelligence. You’ll build systems that generate and use embeddings from images, video, text, and audio at massive scale, then make those signals useful in a real customer-facing search experience. 3. Ship new search capabilities into production. You’ll evaluate models and technologies pragmatically, understand tradeoffs around cost, latency, and quality, and move promising approaches from experiment to a reliable production system within weeks rather than quarters. 4. Own the system end to end. You’ll help shape the problem, gather requirements, design the architecture, write the code, release it, measure the outcome, and improve it. Senior engineers here own results, not just implementation tasks. What the day-to-day looks like Here’s what a typical week might include: • Monday. A customer search is returning technically relevant but unhelpful results. You inspect the retrieval and ranking stages, identify where intent is being lost, and propose a measurable improvement. • Tuesday. Deep-focus time. You build a pipeline to generate multimodal embeddings across a large batch of creator content and test how the new representation affects retrieval quality and cost. • Wednesday. You work with Data Insights on a new in-house datapoint. Together, you agree on its definition, coverage, and data-quality requirements, then expose it in Search to give customers more ways to discover creators. • Thursday. You test a reranking model on a fixed set of real customer queries. You measure how much it improves relevance against the latency and inference cost it adds, then decide what's ready for production. • Friday. You review production metrics, investigate a relevance regression, and share what you learned with the team. The fix may be in the model, the data, the query logic, or the product itself. You follow the evidence. We keep meetings purposeful and protect time for deep work. You’ll have a short standup, close collaboration when it helps, and plenty of space to design, build, optimise, and launch. Requirements What you've done before • Built large-scale data or backend products. You have solid experience working with systems where volume, latency, reliability, and cost all matter. • Shipped products from concept to production. You’ve owned scoping, architecture, implementation, release, measurement, and iteration, not just one layer of the solution. • Designed distributed systems. You can reason clearly about throughput, failure modes, data flow, scalability, and operational tradeoffs. • Built LLM-powered or agentic features in production. You understand the practical differences between models and can balance capability against latency and cost. • Worked autonomously on ambiguous problems. You know how to gather requirements, ask useful questions, and turn incomplete context into forward motion. • Communicated clearly across teams. You can explain technical tradeoffs to engineers and non-engineers, give direct feedback, and collaborate without creating unnecessary …

Hey, I'm Dima . I lead a product engineering team at Modash, and I’m hiring a Senior Product Engineer to help us turn messy customer problems into simple, useful products. Why we're hiring Modash looks simple on the surface. Underneath, it’s a data-heavy product with complex workflows, search, integrations, reporting, automation, attribution, and payments. We have around 20 engineers across four product teams. We need senior engineers who can get close to customers, make product and technical decisions, work across the stack, ship, and stay accountable for whether the solution actually works. This isn’t a narrow frontend or backend role, and it isn’t a ticket factory. You’ll own problems end to end. If you want a feel for how we build software, check our Engineering Blog . What you'll actually own 1. Turn customer pain into product decisions. You’ll understand what users are trying to achieve, where they get stuck, and what the simplest useful solution looks like. You won’t wait for product or design to hand you every answer. 2. Take work from problem to production. You’ll shape the approach, design the system, build across the stack, ship it, measure what happens, and improve it. Senior engineers here own outcomes, not just implementation. 3. Build across deep product surfaces. Depending on the team, you might work on: • Discovery: take a huge creator pool and get a marketer to “these are the ones” fast enough that they start a list, not another search. • CRM: make managing hundreds of creator relationships feel as easy as managing a handful. • Campaigns: turn a flood of creator posts into two answers: did this campaign work, and how do we make the next one better? • Creator: get a sale tracked and the creator paid without invoices, vendor onboarding, or anyone chasing the money. 4. Raise the quality of decisions around you. You’ll ask better questions, challenge weak assumptions, give useful feedback, and help the team move without waiting for perfect certainty. What the day-to-day looks like Here’s what a typical week might include: • Monday. You watch a customer struggle through a campaign workflow and realise the missing button they requested won’t solve the real problem. You map what they’re trying to do and propose a simpler approach. • Tuesday. Deep-focus time. You build the first useful version across Vue and Node.js, including the required data-model changes. • Wednesday. You review the approach with product and design. A polished concept would take six weeks; a narrower version could validate the important behaviour in one. You make the tradeoff explicit and get it moving. • Thursday. A third-party integration starts behaving inconsistently. You trace the issue through asynchronous jobs and improve the failure handling for customers. • Friday. You review what happened after launch. Adoption is lower than expected, so you speak with users and ship an improvement rather than declaring the project finished. We keep meetings purposeful and protect time for deep work. You’ll collaborate closely with engineers, product, and design, while having the autonomy to create clarity and move work forward. Requirements What you've done before • Built products real users depend on. You care about reliability, customer impact, and what happens after deployment. • Developed real backend depth. You can design and debug production services, APIs, data models, asynchronous workflows, and integrations. This usually means at least a couple of years of hands-on backend work. • Worked across the stack. You’re comfortable moving between frontend, backend, infrastructure, data modelling, and product decisions. • Owned ambiguous problems. You gather context, ask useful questions, make tradeoffs, and create clarity without waiting for a detailed specification. • Optimised for product outcomes. You care about technical quality without pursuing elegance at the expense of usefulness or momentum. • Worked closely with product and design. You contribute to the solution and care about the quality of the customer experience. • Used AI as an engineering tool. You use LLMs to prototype, investigate, debug, and improve what you ship—not to avoid thinking. Bonus points if you’ve worked with data-heavy systems, complex workflows, integrations, automation, marketplaces, e-commerce, marketing tools, or the creator economy. Our stack • Infrastructure: AWS—including ECS, Lambda, S3, CloudFront, SQS, EventBridge, and Step Functions—with Pulumi • Persistence and analytics: MongoDB and ClickHouse • Backend: Node.js and TypeScript • Frontend: Vue.js 3, TanStack, and Pinia • Tooling: Cursor, GitHub, Linear, Notion, and Slack The interview process We want the process to show you what engineering at Modash is actually like and give you a clear chance to demonstrate how you think and work. Read about the interview stages and how to prepare . Benefits What we offer • Fully remote in Europe Work …