[Hiring] Senior Software Engineer @Modash

Role Description

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.

Behind that product is a fascinating search problem: helping customers find the right people across 400M+ creator profiles and billions of media files. We’re combining large-scale data processing, traditional retrieval, vector search, multimodal embeddings, and LLMs to make that possible.

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.

What you'll actually own

• Make creator search meaningfully better.
• Turn multimodal data into searchable intelligence.
• Ship new search capabilities into production.
• Own the system end to end.

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.

Qualifications

• Built large-scale data or backend products.
• Shipped products from concept to production.
• Designed distributed systems.
• Built LLM-powered or agentic features in production.
• Worked autonomously on ambiguous problems.
• Communicated clearly across teams.
• Worked in a fast-moving product environment.

Bonus Points

• Experience with multimodal embeddings, vector databases, semantic search, ranking algorithms, model deployment, self-hosted models, or GPU infrastructure.
• Curiosity about the creator economy.

Our Stack

• AWS and GCP, with Pulumi for infrastructure as code
• Python, TypeScript, and Node.js
• PySpark on AWS EMR
• Airflow
• Milvus Vector DB through Zilliz
• Elasticsearch
• LLM batch APIs
• Apache Iceberg
• SageMaker, DynamoDB, S3, Glue, Kinesis, Lambda, ECS, and Aurora
• Slack, GitHub, Linear, Notion, and Cursor

The Interview Process

• Intro chat
• Coding interview
• System design interview
• Team interview
• Culture and alignment conversation with our CEO, Avery Schrader

Benefits

• Fully remote in Europe 🏠 Work from wherever you do your best work, with some overlap with GMT+3.
• Compensation: Your compensation is made up of salary and stock options. Annual salary range is 100,000€ - 130,000€ for this role.
• Flexible hours ⏱ We care about outcomes, not when you log on.
• Unlimited paid vacation 🌴 If you’re rested and happy, you do better work. Take what you need.
• Personal development support 🧠 Courses, books, and conferences are on us when they help you grow.
• Real ownership 💡 Take difficult search problems from idea to production without layers of unnecessary process.
• Regular offsites ✈️ We’re remote-first, but we make time to connect, collaborate, and have fun together in person.